TY - JOUR
AB - AbstractApproximation of subdifferentials is one of the main tasks when computing descent directions for nonsmooth optimization problems. In this article, we propose a bisection method for weakly lower semismooth functions which is able to compute new subgradients that improve a given approximation in case a direction with insufficient descent was computed. Combined with a recently proposed deterministic gradient sampling approach, this yields a deterministic and provably convergent way to approximate subdifferentials for computing descent directions.
AU - Gebken, Bennet
ID - 51208
JF - Computational Optimization and Applications
KW - Applied Mathematics
KW - Computational Mathematics
KW - Control and Optimization
SN - 0926-6003
TI - A note on the convergence of deterministic gradient sampling in nonsmooth optimization
ER -
TY - JOUR
AB - In applications of piezoelectric actuators and sensors, the dependability and particularly the reliability throughout their lifetime are vital to manufacturers and end-users and are enabled through condition-monitoring approaches. Existing approaches often utilize impedance measurements over a range of frequencies or velocity measurements and require additional equipment or sensors, such as a laser Doppler vibrometer. Furthermore, the non-negligible effects of varying operating conditions are often unconsidered. To minimize the need for additional sensors while maintaining the dependability of piezoelectric bending actuators irrespective of varying operating conditions, an online diagnostics approach is proposed. To this end, time- and frequency-domain features are extracted from monitored current signals to reflect hairline crack development in bending actuators. For validation of applicability, the presented analysis method was evaluated on piezoelectric bending actuators subjected to accelerated lifetime tests at varying voltage amplitudes and under external damping conditions. In the presence of a crack and due to a diminished stiffness, the resonance frequency decreases and the root-mean-square amplitude of the current signal simultaneously abruptly drops during the lifetime tests. Furthermore, the piezoelectric crack surfaces clapping is reflected in higher harmonics of the current signal. Thus, time-domain features and harmonics of the current signals are sufficient to diagnose hairline cracks in the actuators.
AU - Aimiyekagbon, Osarenren Kennedy
AU - Bender, Amelie
AU - Hemsel, Tobias
AU - Sextro, Walter
ID - 51518
IS - 3
JF - Electronics
KW - piezoelectric transducer
KW - self-sensing
KW - fault detection
KW - diagnostics
KW - hairline crack
KW - condition monitoring
SN - 2079-9292
TI - Diagnostics of Piezoelectric Bending Actuators Subjected to Varying Operating Conditions
VL - 13
ER -
TY - JOUR
AB - Heteroclinic structures organize global features of dynamical systems. We analyse whether heteroclinic structures can arise in network dynamics with higher-order interactions which describe the nonlinear interactions between three or more units. We find that while commonly analysed model equations such as network dynamics on undirected hypergraphs may be useful to describe local dynamics such as cluster synchronization, they give rise to obstructions that allow to design of heteroclinic structures in phase space. By contrast, directed hypergraphs break the homogeneity and lead to vector fields that support heteroclinic structures.
AU - Bick, Christian
AU - von der Gracht, Sören
ID - 52726
IS - 2
JF - Journal of Complex Networks
KW - Applied Mathematics
KW - Computational Mathematics
KW - Control and Optimization
KW - Management Science and Operations Research
KW - Computer Networks and Communications
SN - 2051-1329
TI - Heteroclinic dynamics in network dynamical systems with higher-order interactions
VL - 12
ER -
TY - CONF
AB - Artificial benchmark functions are commonly used in optimization research because of their ability to rapidly evaluate potential solutions, making them a preferred substitute for real-world problems. However, these benchmark functions have faced criticism for their limited resemblance to real-world problems. In response, recent research has focused on automatically generating new benchmark functions for areas where established test suites are inadequate. These approaches have limitations, such as the difficulty of generating new benchmark functions that exhibit exploratory landscape analysis (ELA) features beyond those of existing benchmarks.The objective of this work is to develop a method for generating benchmark functions for single-objective continuous optimization with user-specified structural properties. Specifically, we aim to demonstrate a proof of concept for a method that uses an ELA feature vector to specify these properties in advance. To achieve this, we begin by generating a random sample of decision space variables and objective values. We then adjust the objective values using CMA-ES until the corresponding features of our new problem match the predefined ELA features within a specified threshold. By iteratively transforming the landscape in this way, we ensure that the resulting function exhibits the desired properties. To create the final function, we use the resulting point cloud as training data for a simple neural network that produces a function exhibiting the target ELA features. We demonstrate the effectiveness of this approach by replicating the existing functions of the well-known BBOB suite and creating new functions with ELA feature values that are not present in BBOB.
AU - Prager, Raphael Patrick
AU - Dietrich, Konstantin
AU - Schneider, Lennart
AU - Schäpermeier, Lennart
AU - Bischl, Bernd
AU - Kerschke, Pascal
AU - Trautmann, Heike
AU - Mersmann, Olaf
ID - 47522
KW - Benchmarking
KW - Instance Generator
KW - Black-Box Continuous Optimization
KW - Exploratory Landscape Analysis
KW - Neural Networks
SN - 9798400702020
T2 - Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms
TI - Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features
ER -
TY - CONF
AB - Evolutionary algorithms have been shown to obtain good solutions for complex optimization problems in static and dynamic environments. It is important to understand the behaviour of evolutionary algorithms for complex optimization problems that also involve dynamic and/or stochastic components in a systematic way in order to further increase their applicability to real-world problems. We investigate the node weighted traveling salesperson problem (W-TSP), which provides an abstraction of a wide range of weighted TSP problems, in dynamic settings. In the dynamic setting of the problem, items that have to be collected as part of a TSP tour change over time. We first present a dynamic setup for the dynamic W-TSP parameterized by different types of changes that are applied to the set of items to be collected when traversing the tour. Our first experimental investigations study the impact of such changes on resulting optimized tours in order to provide structural insights of optimization solutions. Afterwards, we investigate simple mutation-based evolutionary algorithms and study the impact of the mutation operators and the use of populations with dealing with the dynamic changes to the node weights of the problem.
AU - Bossek, Jakob
AU - Neumann, Aneta
AU - Neumann, Frank
ID - 48869
KW - dynamic optimization
KW - evolutionary algorithms
KW - re-optimization
KW - weighted traveling salesperson problem
SN - 9798400701191
T2 - Proceedings of the Genetic and Evolutionary Computation Conference
TI - On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem
ER -
TY - CHAP
AB - This chapter presents a discussion of the concept of agency. Agency is understood as a multifaceted construct describing the idea that human beings make choices, act on these choices, and thereby exercise influence on their own lives as well as their environment. We argue that the concept is discussed from three different perspectives in the literature—transformational, dispositional, and relational—that are each related to learning and development in work contexts. These perspectives do not reflect incompatible positions but rather different aspects of the same phenomena. The chapter also offers an avenue of insight into empirical studies that employ agency as a central concept as well as discussions about concepts that closely overlap with ideas of human beings as agents of power and influence.
AU - Goller, Michael
AU - Paloniemi, Susanna
ID - 30289
KW - Agency Workplace learning Professional development Proactivity Self-direction
SN - 2210-5549
T2 - Research Approaches on Workplace Learning
TI - Agency: Taking Stock of Workplace Learning Research
ER -
TY - CHAP
AB - The article explores the particular quality of changes introduced through the latest wave of digital transformation of workplaces. It has effects on workflow processes, on distribution of work and tasks, and the mode of distributing working tasks, e.g. through cyber-physical systems. Hence, the changes in work are manifold and require changes in vocational education and training as well as in workplace learning. These changes reveal new challenges for research on workplace learning. Finally, conclusions for future workplace learning research will be developed.
AU - Harteis, Christian
ID - 30290
KW - Digitalisation Self organisation Distribution of labour Automation
SN - 2210-5549
T2 - Research Approaches on Workplace Learning
TI - Research on Workplace Learning in Times of Digitalisation
ER -
TY - JOUR
AB - AbstractWe consider the problem of maximization of metabolite production in bacterial cells formulated as a dynamical optimal control problem (DOCP). According to Pontryagin’s maximum principle, optimal solutions are concatenations of singular and bang arcs and exhibit the chattering or Fuller phenomenon, which is problematic for applications. To avoid chattering, we introduce a reduced model which is still biologically relevant and retains the important structural features of the original problem. Using a combination of analytical and numerical methods, we show that the singular arc is dominant in the studied DOCPs and exhibits the turnpike property. This property is further used in order to design simple and realistic suboptimal control strategies.
AU - Caillau, Jean-Baptiste
AU - Djema, Walid
AU - Gouzé, Jean-Luc
AU - Maslovskaya, Sofya
AU - Pomet, Jean-Baptiste
ID - 30861
JF - Journal of Optimization Theory and Applications
KW - Applied Mathematics
KW - Management Science and Operations Research
KW - Control and Optimization
SN - 0022-3239
TI - Turnpike Property in Optimal Microbial Metabolite Production
ER -
TY - CONF
AB - To build successful software products, developers continuously have to discover what features the users really need. This discovery can be achieved with continuous experimentation, testing different software variants with distinct user groups, and deploying the superior variant for all users. However, existing approaches do not focus on explicit modeling of variants and experiments, which offers advantages such as traceability of decisions and combinability of experiments. Therefore, our vision is the provision of model-driven continuous experimentation, which provides the developer with a framework for structuring the experimentation process. For that, we introduce the overall concept, apply it to the experimentation on component-based software architectures and point out future research questions. In particular, we show the applicability by combining feature models for modeling the software variants, users, and experiments (i.e., model-driven) with MAPE-K for the adaptation (i.e., continuous experimentation) and implementing the concept based on the component-based Angular framework.
AU - Gottschalk, Sebastian
AU - Yigitbas, Enes
AU - Engels, Gregor
ID - 29842
KW - continuous experimentation
KW - model-driven
KW - component-based software architectures
KW - self-adaptation
T2 - Proceedings of the 18th International Conference on Software Architecture Companion
TI - Model-driven Continuous Experimentation on Component-based Software Architectures
ER -
TY - JOUR
AB - Mit steigenden Optimierungsanforderungen an das Individuum wächst auch das indivi-
duelle Bedürfnis nach Kontrolle. Dieses kann u. a. durch self tracking-Technologien erfüllt werden.
Anhand von drei Fallbeispielen – der Personenwaage, dem Wearable und dem habit tracker – zeigt
dieser Aufsatz, wie sich medienbasierte Selbsttechnologien im historischen Verlauf intensiviert und
stärker in den Alltag integriert haben. Ein besonderer Fokus liegt dabei auf der Ambivalenz dieser
Medien: Ermöglichen sie auf der einen Seite zwar eine Selbstkontrolle und stellen so potenziell sta-
bilisierende Ressourcen für das Individuum dar, schaffen sie auf der anderen Seite auch neue
Anforderungen, die es zu erfüllen gilt.
AU - Schloots, Franziska Margarete
ID - 34614
IS - 7
JF - ffk Journal
KW - self-tracking
KW - Selbsttechnologien
KW - Wearable
KW - Bullet Journal
KW - Personenwaage
KW - Selbstvermessung
TI - ‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker
VL - 6
ER -
TY - JOUR
AB - Im Zentrum dieses Beitrags stehen Ergebnisse der Messung pädagogischer Kompetenzen Studierender der Theologie, die das Praxissemester in Deutschland absolviert haben. Das bildungswissenschaftliche Wissen, Kompetenzselbsteinschätzungen und ihre Entwicklung sowie die Einschätzung der im Praxissemester erreichten Ziele Studierender werden dabei unter Berücksichtigung der Ausrichtung des Lehramtsstudiums auf eine Schulform betrachtet. Um die Ergebnisse der Messung bildungswissenschaftlichen Wissens und die der Messung von Kompetenzselbsteinschätzungen zu kontextualisieren (N = 304), wird zuerst die Relevanz des (bildungswissenschaftlichen) Wissens als Ausgangspunkt des Könnens herausgearbeitet. Daran anschließend werden Befunde zur schulformspezifischen Professionalisierung resümiert. Anschließend werden Hypothesen hergeleitet, die Anlage der Studie sowie die Testinstrumente vorge- stellt, die Ergebnisse präsentiert und diskutiert. Die Ergebnisse zeigen wider Erwarten, dass sich weder das bildungswissenschaftliche Wissen, die Kompetenzselbsteinschätzungen und ihre Entwicklung noch die Einschätzung der im Praxissemester erreichten Ziele angehender Lehrkräfte in Abhängigkeit der Schulformen unterscheiden. Die Diskussion bezieht sich u.a. auf die Struktur der Lehramtsstudiengänge, die Denkfiguren zur Entwicklung von Können und die Konzeption der Messinstrumente.
AU - Caruso, Carina
AU - Seifert, Andreas
ID - 35136
IS - 1
JF - Österreichische Religionspädagogische Forum
KW - Bildungswissenschaftliches Wissen
KW - Kompetenzmessung
KW - Kompetenzselbsteinschätzung
KW - Praxissemester
KW - Professionalisierung / competence measurement
KW - competence self-assessment
KW - educational knowledge
KW - internship
KW - professionalization
SN - 1018-1539
TI - Inwiefern ist die Professionalisierung in Praxisphasen schulformspezifisch?
VL - 30
ER -
TY - JOUR
AB - Im Zentrum dieses Beitrags stehen Ergebnisse der Messung pädagogischer Kompetenzen Studierender. Dabei werden sowohl das bildungswissenschaftliche Wissen als auch die Entwicklung der Kompetenzselbsteinschätzungen in den Bereichen Unterrichten, Erziehen, Beurteilen und Innovieren unter Berücksichtigung individueller Voraussetzungen (Alter, Geschlecht, Abiturnote, Bachelornote, Konfession) betrachtet. Um die Ergebnisse hinsichtlich ihrer Bedeutung für die Professionalisierung angehender Lehrkräfte diskutieren zu können, wird, den empirischen Erkenntnissen voranstehend, die Bedeutung von Wissen für berufliches Können herausgearbeitet. Daran anschließend werden Hypothesen hergeleitet, die Anlage der Studie sowie die Testinstrumente vorgestellt, die Ergebnisse präsentiert und diskutiert. Die Ergebnisse zeigen, dass die Abitur- und Bachelornote die Varianz hinsichtlich des pädagogischen Wissens aufklären, sich eine signifikante Entwicklung der Kompetenzselbsteinschätzungen angehender Lehrkräfte feststellen lässt, aber sich angehende Religionslehrkräfte kaum von anderen Studierenden unterscheiden. Die Diskussion nimmt u. a. Rückbezug auf die Denkfiguren zur Entwicklung beruflichen Könnens und benennt Limitationen, die mit der Studie und Kompetenzmessungen verbunden sind. Daran schließt die Formulierung eines Ausblicks an. Der Beitrag zielt insbesondere darauf, repräsentative Ergebnisse der Kompetenzmessung zu präsentieren und dabei potenzielle Einflussfaktoren auf die studentische Kompetenzentwicklung zu beleuchten. Ein dadurch angereichertes Konglomerat belastbarer Erkenntnisse zielt darauf, langfristig zur Ableitung lehrerbildungsdidaktischer Überlegungen herangezogen werden zu können, die die studentische Professionalisierung unterstützen.
AU - Caruso, Carina
AU - Seifert, Andreas
ID - 35137
IS - 1
JF - Religionspädagogische Beiträge. Journal for Religion in Education
KW - Bildungswissenschaftliches Wissen
KW - Kompetenzmessung
KW - Kompetenzselbsteinschätzung
KW - Praxissemester
KW - Professionalisierung / competence measurement
KW - competence self-assessment
KW - educational knowledge
KW - internship
KW - professionalization
SN - 2750 - 3941
TI - Pädagogische Kompetenz als Ausgangspunkt beruflichen Könnens!? Ergebnisse der Kompetenzmessung angehender Lehrkräfte unter Berücksichtigung individueller Voraussetzungen
VL - 45
ER -
TY - JOUR
AU - Bonnard, Bernard
AU - Rouot, Jérémy
AU - Wembe Moafo, Boris Edgar
ID - 35206
JF - Mathematical Control and Related Fields
KW - Applied Mathematics
KW - Control and Optimization
KW - General Medicine
SN - 2156-8472
TI - Accessibility properties of abnormal geodesics in optimal control illustrated by two case studies
ER -
TY - CONF
AB - Theoretical approaches to the transformation towards an inclusive educational system in Germany mostly agree on the involvement of developmental tasks in subject related research (Hinz, 2011). The common understanding of inclusion as a process geared towards equal participation of all children (Booth, 2012) requires a reflexive questioning of established values, attitudes and practices in order to develop inclusive subject related research, teacher training and teaching and learning (Pech & Schomaker, 2013). Among other things, this results in consequences for the design of pre- service teacher training. To a large extent, teacher education is driven by the promotion of central competencies, interests and self-efficacy (Baumert & Kunter, 2011). It aims towards the development and realisation of inclusive interdisciplinary science and social studies (‘Sachunterricht’) in primary education (Moser, 2018). In conjunction with largely acknowledged constructivist approaches to teaching and learning (Möller, 2001), the development of personality, the consideration of basic needs (Deci & Ryan, 1993) and promotion of individual potentials are repeatedly fundamentally represented in subject related and pedagogical considerations (Feuser, 1989; GDSU, 2013). Therefore, the aforementioned constructivist approach is connected to several certain key paradigms for teaching and learning processes (e.g., Vygotskij, 1978; Posner et al., 1982; van de Pol et al., 2010). In this regard, the nature of primary school students’ basic needs have empirically not been sufficiently studied yet. Theoretical frameworks from motivational psychology (Deci & Ryan, 1993) do not explicitly address how individual needs differ and how the diversity of needs can be included in joint-learning, multi-perspective technology education classes. The research project the present paper is part of aims to develop a research-based concept for the professionalisation of pre-service teachers in a seminar course. Therefore, the promotion of the pre- service teachers’ interests and self-efficacy expectations have been assessed in a pre-post research design with a control group visiting another course not related to technology education and inclusion. The present paper describes and discusses first results of the project and will give an outlook on subsequent developmental tasks.
AU - Schröer, Franz
AU - Tenberge, Claudia
ED - Gill, David
ED - Tuff, Jim
ED - Kennedy, Thomas
ED - Pendergast, Shawn
ED - Jamil, Sana
ID - 40046
KW - Inclusion
KW - basic needs
KW - pre-service teacher training
KW - interest
KW - self-efficacy
T2 - PATT39 - PATT on the Edge Technology, Innovation and Education
TI - How to enable pre-service teachers to design technological teaching and learning inclusively? – On the nature and consideration of basic needs in teacher training
ER -
TY - JOUR
AU - Constantiou, Ioanna
AU - Mukkamala, Alivelu
AU - Sjöklint, Mimmi
AU - Trier, Matthias
ID - 36083
JF - European Journal of Information Systems
KW - Library and Information Sciences
KW - Information Systems
KW - Self-Tracking
KW - User Behaviour
KW - Discontinuance
SN - 0960-085X
TI - Engaging with self-tracking applications: how do users respond to their performance data?
ER -
TY - CONF
AB - While trade-offs between modeling effort and model accuracy remain a major concern with system identification, resorting to data-driven methods often leads to a complete disregard for physical plausibility. To address this issue, we propose a physics-guided hybrid approach for modeling non-autonomous systems under control. Starting from a traditional physics-based model, this is extended by a recurrent neural network and trained using a sophisticated multi-objective strategy yielding physically plausible models. While purely data-driven methods fail to produce satisfying results, experiments conducted on real data reveal substantial accuracy improvements by our approach compared to a physics-based model.
AU - Schön, Oliver
AU - Götte, Ricarda-Samantha
AU - Timmermann, Julia
ID - 31066
IS - 12
KW - neural networks
KW - physics-guided
KW - data-driven
KW - multi-objective optimization
KW - system identification
KW - machine learning
KW - dynamical systems
T2 - 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)
TI - Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems
VL - 55
ER -
TY - JOUR
AB - Due to failures or even the absence of an electricity grid, microgrid systems are becoming popular solutions for electrifying African rural communities. However, they are heavily stressed and complex to control due to their intermittency and demand growth. Demand side management (DSM) serves as an option to increase the level of flexibility on the demand side by scheduling users’ consumption patterns profiles in response to supply. This paper proposes a demand-side management strategy based on load shifting and peak clipping. The proposed approach was modelled in a MATLAB/Simulink R2021a environment and was optimized using the artificial neural network (ANN) algorithm. Simulations were carried out to test the model’s efficacy in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces the peak demand, smoothing the load profile to the desired level, and improves the system’s peak to average ratio (PAR). The presence of deferrable loads has been considered to bring more flexible demand-side management. Results promise decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through peak clipping. In addition, load shifting promises more flexibility to customers.
AU - Philipo, Godiana Hagile
AU - Kakande, Josephine Nakato
AU - Krauter, Stefan
ID - 32403
IS - 14
JF - Energies
KW - Energy (miscellaneous)
KW - Energy Engineering and Power Technology
KW - Renewable Energy
KW - Sustainability and the Environment
KW - Electrical and Electronic Engineering
KW - Control and Optimization
KW - Engineering (miscellaneous)
KW - Building and Construction
SN - 1996-1073
TI - Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping
VL - 15
ER -
TY - JOUR
AB - Due to failures or even the absence of an electricity grid, microgrid systems are becoming popular solutions for electrifying African rural communities. However, they are heavily stressed and complex to control due to their intermittency and demand growth. Demand side management (DSM) serves as an option to increase the level of flexibility on the demand side by scheduling users’ consumption patterns profiles in response to supply. This paper proposes a demand-side management strategy based on load shifting and peak clipping. The proposed approach was modelled in a MATLAB/Simulink R2021a environment and was optimized using the artificial neural network (ANN) algorithm. Simulations were carried out to test the model’s efficacy in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces the peak demand, smoothing the load profile to the desired level, and improves the system’s peak to average ratio (PAR). The presence of deferrable loads has been considered to bring more flexible demand-side management. Results promise decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through peak clipping. In addition, load shifting promises more flexibility to customers.
AU - Philipo, Godiana Hagile
AU - Kakande, Josephine Nakato
AU - Krauter, Stefan
ID - 47961
IS - 14
JF - Energies
KW - Energy (miscellaneous)
KW - Energy Engineering and Power Technology
KW - Renewable Energy
KW - Sustainability and the Environment
KW - Electrical and Electronic Engineering
KW - Control and Optimization
KW - Engineering (miscellaneous)
KW - Building and Construction
SN - 1996-1073
TI - Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping
VL - 15
ER -
TY - CONF
AB - Ultrasonic wire bonding is a solid-state joining process used to form electrical interconnections in micro and
power electronics and batteries. A high frequency oscillation causes a metallurgical bond deformation in
the contact area. Due to the numerous physical influencing factors, it is very difficult to accurately capture
this process in a model. Therefore, our goal is to determine a suitable feed-forward control strategy for the
bonding process even without detailed model knowledge. We propose the use of batch constrained Bayesian
optimization for the control design. Hence, Bayesian optimization is precisely adapted to the application of
bonding: the constraint is used to check one quality feature of the process and the use of batches leads to
more efficient experiments. Our approach is suitable to determine a feed-forward control for the bonding
process that provides very high quality bonds without using a physical model. We also show that the quality
of the Bayesian optimization based control outperforms random search as well as manual search by a user.
Using a simple prior knowledge model derived from data further improves the quality of the connection.
The Bayesian optimization approach offers the possibility to perform a sensitivity analysis of the control
parameters, which allows to evaluate the influence of each control parameter on the bond quality. In summary,
Bayesian optimization applied to the bonding process provides an excellent opportunity to develop a feedforward
control without full modeling of the underlying physical processes.
AU - Hesse, Michael
AU - Hunstig, Matthias
AU - Timmermann, Julia
AU - Trächtler, Ansgar
ID - 29803
KW - Bayesian optimization
KW - Wire bonding
KW - Feed-forward control
KW - model-free design
SN - 978-989-758-549-4
T2 - Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM)
TI - Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design
ER -
TY - CONF
AB - In multimodal multi-objective optimization (MMMOO), the focus is not solely on convergence in objective space, but rather also on explicitly ensuring diversity in decision space. We illustrate why commonly used diversity measures are not entirely appropriate for this task and propose a sophisticated basin-based evaluation (BBE) method. Also, BBE variants are developed, capturing the anytime behavior of algorithms. The set of BBE measures is tested by means of an algorithm configuration study. We show that these new measures also transfer properties of the well-established hypervolume (HV) indicator to the domain of MMMOO, thus also accounting for objective space convergence. Moreover, we advance MMMOO research by providing insights into the multimodal performance of the considered algorithms. Specifically, algorithms exploiting local structures are shown to outperform classical evolutionary multi-objective optimizers regarding the BBE variants and respective trade-off with HV.
AU - Heins, Jonathan
AU - Rook, Jeroen
AU - Schäpermeier, Lennart
AU - Kerschke, Pascal
AU - Bossek, Jakob
AU - Trautmann, Heike
ED - Rudolph, Günter
ED - Kononova, Anna V.
ED - Aguirre, Hernán
ED - Kerschke, Pascal
ED - Ochoa, Gabriela
ED - Tusar, Tea
ID - 48882
KW - Anytime behavior
KW - Benchmarking
KW - Continuous optimization
KW - Multi-objective optimization
KW - Multimodality
KW - Performance metric
SN - 978-3-031-14714-2
T2 - Parallel Problem Solving from Nature (PPSN XVII)
TI - BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems
ER -
TY - CONF
AB - Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.
AU - Rook, Jeroen
AU - Trautmann, Heike
AU - Bossek, Jakob
AU - Grimme, Christian
ID - 48896
KW - configuration
KW - multi-modality
KW - multi-objective optimization
SN - 978-1-4503-9268-6
T2 - Proceedings of the Genetic and Evolutionary Computation Conference Companion
TI - On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems
ER -
TY - JOUR
AB - Automated machine learning (AutoML) supports the algorithmic construction and data-specific customization of machine learning pipelines, including the selection, combination, and parametrization of machine learning algorithms as main constituents. Generally speaking, AutoML approaches comprise two major components: a search space model and an optimizer for traversing the space. Recent approaches have shown impressive results in the realm of supervised learning, most notably (single-label) classification (SLC). Moreover, first attempts at extending these approaches towards multi-label classification (MLC) have been made. While the space of candidate pipelines is already huge in SLC, the complexity of the search space is raised to an even higher power in MLC. One may wonder, therefore, whether and to what extent optimizers established for SLC can scale to this increased complexity, and how they compare to each other. This paper makes the following contributions: First, we survey existing approaches to AutoML for MLC. Second, we augment these approaches with optimizers not previously tried for MLC. Third, we propose a benchmarking framework that supports a fair and systematic comparison. Fourth, we conduct an extensive experimental study, evaluating the methods on a suite of MLC problems. We find a grammar-based best-first search to compare favorably to other optimizers.
AU - Wever, Marcel Dominik
AU - Tornede, Alexander
AU - Mohr, Felix
AU - Hüllermeier, Eyke
ID - 21004
JF - IEEE Transactions on Pattern Analysis and Machine Intelligence
KW - Automated Machine Learning
KW - Multi Label Classification
KW - Hierarchical Planning
KW - Bayesian Optimization
SN - 0162-8828
TI - AutoML for Multi-Label Classification: Overview and Empirical Evaluation
ER -
TY - JOUR
AB - Modern services consist of interconnected components,e.g., microservices in a service mesh or machine learning functions in a pipeline. These services can scale and run across multiple network nodes on demand. To process incoming traffic, service components have to be instantiated and traffic assigned to these instances, taking capacities, changing demands, and Quality of Service (QoS) requirements into account. This challenge is usually solved with custom approaches designed by experts. While this typically works well for the considered scenario, the models often rely on unrealistic assumptions or on knowledge that is not available in practice (e.g., a priori knowledge).
We propose DeepCoord, a novel deep reinforcement learning approach that learns how to best coordinate services and is geared towards realistic assumptions. It interacts with the network and relies on available, possibly delayed monitoring information. Rather than defining a complex model or an algorithm on how to achieve an objective, our model-free approach adapts to various objectives and traffic patterns. An agent is trained offline without expert knowledge and then applied online with minimal overhead. Compared to a state-of-the-art heuristic, DeepCoord significantly improves flow throughput (up to 76%) and overall network utility (more than 2x) on realworld network topologies and traffic traces. It also supports optimizing multiple, possibly competing objectives, learns to respect QoS requirements, generalizes to scenarios with unseen, stochastic traffic, and scales to large real-world networks. For reproducibility and reuse, our code is publicly available.
AU - Schneider, Stefan Balthasar
AU - Khalili, Ramin
AU - Manzoor, Adnan
AU - Qarawlus, Haydar
AU - Schellenberg, Rafael
AU - Karl, Holger
AU - Hecker, Artur
ID - 21808
JF - Transactions on Network and Service Management
KW - network management
KW - service management
KW - coordination
KW - reinforcement learning
KW - self-learning
KW - self-adaptation
KW - multi-objective
TI - Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning
ER -
TY - GEN
AB - Macrodiversity is a key technique to increase the capacity of mobile networks. It can be realized using coordinated multipoint (CoMP), simultaneously connecting users to multiple overlapping cells. Selecting which users to serve by how many and which cells is NP-hard but needs to happen continuously in real time as users move and channel state changes. Existing approaches often require strict assumptions about or perfect knowledge of the underlying radio system, its resource allocation scheme, or user movements, none of which is readily available in practice.
Instead, we propose three novel self-learning and self-adapting approaches using model-free deep reinforcement learning (DRL): DeepCoMP, DD-CoMP, and D3-CoMP. DeepCoMP leverages central observations and control of all users to select cells almost optimally. DD-CoMP and D3-CoMP use multi-agent DRL, which allows distributed, robust, and highly scalable coordination. All three approaches learn from experience and self-adapt to varying scenarios, reaching 2x higher Quality of Experience than other approaches. They have very few built-in assumptions and do not need prior system knowledge, making them more robust to change and better applicable in practice than existing approaches.
AU - Schneider, Stefan Balthasar
AU - Karl, Holger
AU - Khalili, Ramin
AU - Hecker, Artur
ID - 33854
KW - mobility management
KW - coordinated multipoint
KW - CoMP
KW - cell selection
KW - resource management
KW - reinforcement learning
KW - multi agent
KW - MARL
KW - self-learning
KW - self-adaptation
KW - QoE
TI - DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning
ER -
TY - JOUR
AB - With the rapid progress of technological development, self-efficacy in reference to digital devices (i.e., information and computer technology [ICT] self-efficacy) is an important driver that helps students to deal with technological problems and support their lifelong learning processes. Schools, peers, and home learning environments are important sources for the development of positive self-efficacy. Expanding on previous research, we investigated the associations between different aspects of the digital home learning environment and students’ ICT self-efficacy. The moderation effects of gender were also tested. A total of 651 children answered a questionnaire about different digital home learning environment dimensions and estimated their ICT self-efficacy using an adapted scale—Schwarzer and Jerusalem’s (1999) general self-efficacy scale. Using the structural equation modeling technique, a digital home learning environment containing six different qualities of parental support was investigated. Families’ cultural capital, parents’ attitudes toward the Internet, and shared Internet activities at home contributed positively to ICT self-efficacy. We observed small gender differences, with the moderation effect being nonsignificant. The results help researchers and practitioners to understand how different dimensions of the digital home learning environment support ICT self-efficacy. We will discuss how parents can enhance the home learning environment and how teachers can integrate this knowledge into formal education.
AU - Bonanati, Sabrina
AU - Buhl, Heike M.
ID - 32558
IS - 2
JF - Learning Environments Research
KW - Digital media use
KW - Gender
KW - Home learning environment
KW - ICT self-efcacy
KW - Motivation
KW - Parental involvement
SN - 1387-1579
TI - The digital home learning environment and its relation to children’s ICT self-efficacy
VL - 25
ER -
TY - GEN
AB - This study examines the relation between voluntary audit and the cost of debt in private firms. We use a sample of 4,058 small private firms operating in the period 2006‐2017 that are not subject to mandatory audits. Firms decide for a voluntary audit of financial statements either because the economic setting in which they operate effectively forces them to do so (e.g., ownership complexity, export‐oriented supply chain, subsidiary status) or because firm fundamentals and/or financial reporting practices limit their access to financial debt, both reflected in earnings quality. We use these factors to model the decision for voluntary audit. In the outcome analyses, we find robust evidence that voluntary audits are associated with higher, rather than lower, interest rate by up to 3.0 percentage points. This effect is present regardless of the perceived audit quality (Big‐4 vs. non‐Big‐4), but is stronger for non‐Big‐4 audits where auditees have a stronger position relative to auditors. Audited firms’ earnings are less informative about future operating performance relative to unaudited counterparts. We conclude that voluntary audits facilitate access to financial debt for firms with higher risk that may otherwise have no access to this form of financing. The price paid is reflected in higher interest rates charged to firms with voluntary audits – firms with higher information and/or fundamental risk.
AU - Ichev, Riste
AU - Koren, Jernej
AU - Kosi, Urska
AU - Sitar Sustar, Katarina
AU - Valentincic, Aljosa
ID - 37136
KW - private firms
KW - voluntary audit
KW - cost of debt
KW - self‐selection bias
KW - risk
TI - Cost of Debt for Private Firms Revisited: Voluntary Audits as a Reflection of Risk
ER -
TY - CHAP
AB - Self-piercing riveting is an established technique for joining multi-material structures in car body manufacturing. Rivets for self-piercing riveting differ in their geometry, the material used, the condition of the material and their surface condition. To shorten the manufacturing process by omitting the heat treatment and the coating process, the authors have elaborated a concept for the use of stainless steel with high strain hardening as a rivet material. The focus of the present investigation is on the evaluation of the influences of the rivet’s geometry and material on its deformation behaviour. Conventional rivets of types P and HD2, a rivet with an improved geometry made of treatable steel 38B2, and rivets made of the stainless steels 1.3815 and 1.4541 are examined. The analysis is conducted by means of multi-step joining tests for two material combinations comprising high-strength steel HCT70X and aluminium EN AW-5083. The joints are cut to provide a cross-section and the deformation behaviour of the different rivets is analysed on the basis of the measured changes in geometry and hardness. In parallel, an examination of the force-stroke curves provides further insights. It can be demonstrated that, besides the geometry, the material strength, in particular, has a significant influence on the deformation behaviour of the rivet. The strength of steel 1.4541 is seen to be too low for the joining task, while the strength of steel 1.3815 is sufficient, and hence the investigation confirms the capability of rivets made of 1.3815 for joining even challenging material combinations.
AU - Uhe, Benedikt
AU - Kuball, Clara-Maria
AU - Merklein, Marion
AU - Meschut, Gerson
ED - Daehn, Glenn
ED - Cao, Jian
ED - Kinsey, Brad
ED - Tekkaya, Erman
ED - Vivek, Anupam
ED - Yoshida, Yoshinori
ID - 22930
KW - Self-piercing riveting
KW - Lightweight design
KW - Deformation behaviour
KW - Stainless steel
KW - High nitrogen steel
T2 - Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals & Materials Series.
TI - Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening
ER -
TY - CONF
AB - The use of high-strength steel and aluminium is rising due to the intensified efforts being made in lightweight design, and self-piercing riveting is becoming increasingly important. Conventional rivets for self-piercing riveting differ in their geometry, the material used, the condition of the material and the coating. To shorten the manufacturing process, the use of stainless steel with high strain hardening as the rivet material represents a promising approach. This allows the coating of the rivets to be omitted due to the corrosion resistance of the material and, since the strength of the stainless steel is achieved by cold forming, heat treatment is no longer required. In addition, it is possible to adjust the local strength within the rivet. Because of that, the authors have elaborated a concept for using high nitrogen steel 1.3815 as the rivet material. The present investigation focusses on the joint strength in order to evaluate the capability of rivets in high nitrogen steel by comparison to conventional rivets made of treatable steel. Due to certain challenges in the forming process of the high nitrogen steel rivets, deviations result from the targeted rivet geometry. Mainly these deviations cause a lower joint strength with these rivets, which is, however, adequate. All in all, the capability of the new rivet is proven by the results of this investigation.
AU - Uhe, Benedikt
AU - Kuball, Clara-Maria
AU - Merklein, Marion
AU - Meschut, Gerson
ID - 22274
KW - Self-piercing Riveting
KW - Joining Technology
KW - Rivet Geometry
KW - Rivet Material
KW - High Nitrogen Steel
KW - Joint Strength
TI - Strength of self-piercing riveted Joints with conventional Rivets and Rivets made of High Nitrogen Steel
ER -
TY - JOUR
AB - Ultrasonic wire bonding is a solid-state joining process, used in the electronics industry to form electrical connections, e.g. to connect electrical terminals within semiconductor modules. Many process parameters affect the bond strength, such like the bond normal force, ultrasonic power, wire material and bonding frequency. Today, process design, development, and optimization is most likely based on the knowledge of process engineers and is mainly performed by experimental testing. In this contribution, a newly developed simulation tool is presented, to reduce time and costs and efficiently determine optimized process parameter. Based on a co-simulation of MATLAB and ANSYS, the different physical phenomena of the wire bonding process are considered using finite element simulation for the complex plastic deformation of the wire and reduced order models for the transient dynamics of the transducer, wire, substrate and bond formation. The model parameters such as the coefficients of friction between bond tool and wire and between wire and substrate were determined for aluminium and copper wire in experiments with a test rig specially developed for the requirements of heavy wire bonding. To reduce simulation time, for the finite element simulation a restart analysis and high performance computing is utilized. Detailed analysis of the bond formation showed, that the normal pressure distribution in the contact between wire and substrate has high impact on bond formation and distribution of welded areas in the contact area.
AU - Schemmel, Reinhard
AU - Krieger, Viktor
AU - Hemsel, Tobias
AU - Sextro, Walter
ID - 21436
JF - Microelectronics Reliability
KW - Ultrasonic heavy wire bonding
KW - Co-simulation
KW - ANSYS
KW - MATLAB
KW - Process optimization
KW - Friction coefficient
KW - Copper-copper
KW - Aluminium-copper
SN - 0026-2714
TI - Co-simulation of MATLAB and ANSYS for ultrasonic wire bonding process optimization
VL - 119
ER -
TY - JOUR
AB - Multi-objective (MO) optimization, i.e., the simultaneous optimization of multiple conflicting objectives, is gaining more and more attention in various research areas, such as evolutionary computation, machine learning (e.g., (hyper-)parameter optimization), or logistics (e.g., vehicle routing). Many works in this domain mention the structural problem property of multimodality as a challenge from two classical perspectives: (1) finding all globally optimal solution sets, and (2) avoiding to get trapped in local optima. Interestingly, these streams seem to transfer many traditional concepts of single-objective (SO) optimization into claims, assumptions, or even terminology regarding the MO domain, but mostly neglect the understanding of the structural properties as well as the algorithmic search behavior on a problem’s landscape. However, some recent works counteract this trend, by investigating the fundamentals and characteristics of MO problems using new visualization techniques and gaining surprising insights. Using these visual insights, this work proposes a step towards a unified terminology to capture multimodality and locality in a broader way than it is usually done. This enables us to investigate current research activities in multimodal continuous MO optimization and to highlight new implications and promising research directions for the design of benchmark suites, the discovery of MO landscape features, the development of new MO (or even SO) optimization algorithms, and performance indicators. For all these topics, we provide a review of ideas and methods but also an outlook on future challenges, research potential and perspectives that result from recent developments.
AU - Grimme, Christian
AU - Kerschke, Pascal
AU - Aspar, Pelin
AU - Trautmann, Heike
AU - Preuss, Mike
AU - Deutz, André H.
AU - Wang, Hao
AU - Emmerich, Michael
ID - 46318
JF - Computers & Operations Research
KW - Multimodal optimization
KW - Multi-objective continuous optimization
KW - Landscape analysis
KW - Visualization
KW - Benchmarking
KW - Theory
KW - Algorithms
SN - 0305-0548
TI - Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization
VL - 136
ER -
TY - CONF
AB - In practise, it is often desirable to provide the decision-maker with a rich set of diverse solutions of decent quality instead of just a single solution. In this paper we study evolutionary diversity optimization for the knapsack problem (KP). Our goal is to evolve a population of solutions that all have a profit of at least (1 - {$ϵ$}) {$\cdot$} OPT, where OPT is the value of an optimal solution. Furthermore, they should differ in structure with respect to an entropy-based diversity measure. To this end we propose a simple ({$\mu$} + 1)-EA with initial approximate solutions calculated by a well-known FPTAS for the KP. We investigate the effect of different standard mutation operators and introduce biased mutation and crossover which puts strong probability on flipping bits of low and/or high frequency within the population. An experimental study on different instances and settings shows that the proposed mutation operators in most cases perform slightly inferior in the long term, but show strong benefits if the number of function evaluations is severely limited.
AU - Bossek, Jakob
AU - Neumann, Aneta
AU - Neumann, Frank
ID - 48853
KW - evolutionary algorithms
KW - evolutionary diversity optimization
KW - knapsack problem
KW - tailored operators
SN - 978-1-4503-8350-9
T2 - Proceedings of the Genetic and Evolutionary Computation Conference
TI - Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms
ER -
TY - CONF
AB - In the area of evolutionary computation the calculation of diverse sets of high-quality solutions to a given optimization problem has gained momentum in recent years under the term evolutionary diversity optimization. Theoretical insights into the working principles of baseline evolutionary algorithms for diversity optimization are still rare. In this paper we study the well-known Minimum Spanning Tree problem (MST) in the context of diversity optimization where population diversity is measured by the sum of pairwise edge overlaps. Theoretical results provide insights into the fitness landscape of the MST diversity optimization problem pointing out that even for a population of {$\mu$} = 2 fitness plateaus (of constant length) can be reached, but nevertheless diverse sets can be calculated in polynomial time. We supplement our theoretical results with a series of experiments for the unconstrained and constraint case where all solutions need to fulfill a minimal quality threshold. Our results show that a simple ({$\mu$} + 1)-EA can effectively compute a diversified population of spanning trees of high quality.
AU - Bossek, Jakob
AU - Neumann, Frank
ID - 48860
KW - evolutionary algorithms
KW - evolutionary diversity optimization
KW - minimum spanning tree
KW - runtime analysis
SN - 978-1-4503-8350-9
T2 - Proceedings of the Genetic and Evolutionary Computation Conference
TI - Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem
ER -
TY - JOUR
AB - We contribute to the theoretical understanding of randomized search heuristics for dynamic problems. We consider the classical vertex coloring problem on graphs and investigate the dynamic setting where edges are added to the current graph. We then analyze the expected time for randomized search heuristics to recompute high quality solutions. The (1+1) Evolutionary Algorithm and RLS operate in a setting where the number of colors is bounded and we are minimizing the number of conflicts. Iterated local search algorithms use an unbounded color palette and aim to use the smallest colors and, consequently, the smallest number of colors. We identify classes of bipartite graphs where reoptimization is as hard as or even harder than optimization from scratch, i.e., starting with a random initialization. Even adding a single edge can lead to hard symmetry problems. However, graph classes that are hard for one algorithm turn out to be easy for others. In most cases our bounds show that reoptimization is faster than optimizing from scratch. We further show that tailoring mutation operators to parts of the graph where changes have occurred can significantly reduce the expected reoptimization time. In most settings the expected reoptimization time for such tailored algorithms is linear in the number of added edges. However, tailored algorithms cannot prevent exponential times in settings where the original algorithm is inefficient.
AU - Bossek, Jakob
AU - Neumann, Frank
AU - Peng, Pan
AU - Sudholt, Dirk
ID - 48854
IS - 10
JF - Algorithmica
KW - Dynamic optimization
KW - Evolutionary algorithms
KW - Running time analysis
SN - 0178-4617
TI - Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem
VL - 83
ER -
TY - CONF
AB - Modern services comprise interconnected components,
e.g., microservices in a service mesh, that can scale and
run on multiple nodes across the network on demand. To process
incoming traffic, service components have to be instantiated and
traffic assigned to these instances, taking capacities and changing
demands into account. This challenge is usually solved with
custom approaches designed by experts. While this typically
works well for the considered scenario, the models often rely
on unrealistic assumptions or on knowledge that is not available
in practice (e.g., a priori knowledge).
We propose a novel deep reinforcement learning approach that
learns how to best coordinate services and is geared towards
realistic assumptions. It interacts with the network and relies on
available, possibly delayed monitoring information. Rather than
defining a complex model or an algorithm how to achieve an
objective, our model-free approach adapts to various objectives
and traffic patterns. An agent is trained offline without expert
knowledge and then applied online with minimal overhead. Compared
to a state-of-the-art heuristic, it significantly improves flow
throughput and overall network utility on real-world network
topologies and traffic traces. It also learns to optimize different
objectives, generalizes to scenarios with unseen, stochastic traffic
patterns, and scales to large real-world networks.
AU - Schneider, Stefan Balthasar
AU - Manzoor, Adnan
AU - Qarawlus, Haydar
AU - Schellenberg, Rafael
AU - Karl, Holger
AU - Khalili, Ramin
AU - Hecker, Artur
ID - 19609
KW - self-driving networks
KW - self-learning
KW - network coordination
KW - service coordination
KW - reinforcement learning
KW - deep learning
KW - nfv
T2 - IEEE International Conference on Network and Service Management (CNSM)
TI - Self-Driving Network and Service Coordination Using Deep Reinforcement Learning
ER -
TY - GEN
AB - The aim to reduce pollutant emission has led to a trend towards lightweight construction in car body development during the last years. As a consequence of the resulting need for multi-material design, mechanical joining technologies become increasingly important. Mechanical joining allows for the combination of dissimilar materials, while thermic joining techniques reach their limits. Self-piercing riveting enables the joining of dissimilar materials by using semi-tubular rivets as mechanical fasteners. The rivet production, however, is costly and time-consuming, as the rivets generally have to be hardened, tempered and coated after forming, in order to achieve an adequate strength and corrosion resistance. A promising approach to improve the efficiency of the rivet manufacturing is the use of high-strength high nitrogen steel as rivet material because these additional process steps would not be necessary anymore. As a result of the comparatively high nitrogen content, such steels have various beneficial properties like higher strength, good ductility and improved corrosion resistance. By cold bulk forming of high nitrogen steels high-strength parts can be manufactured due to the strengthening which is caused by the high strain hardening. However, high tool loads thereby have to be expected and are a major challenge during the production process. Consequently, there is a need for appropriate forming strategies. This paper presents key aspects concerning the process design for the manufacturing of semi-tubular self-piercing rivets made of high-strength steel. The aim is to produce the rivets in several forming stages without intermediate heat treatment between the single stages. Due to the high strain hardening of the material, a two stage forming concept will be investigated. Cup-backward extrusion is chosen as the first process step in order to form the rivet shank without forming the rivet foot. Thus, the strain hardening effects in the area of the rivet foot are minimized and the tool loads during the following process step can be reduced. During the second and final forming stage the detailed geometry of the rivet foot and the rivet head is formed. In this context, the effect of different variations, for example concerning the final geometry of the rivet foot, on the tool load is investigated using multistage numerical analysis. Furthermore, the influence of the process temperature on occurring stresses is analysed. Based on the results of the investigations, an adequate forming strategy and a tool concept for the manufacturing of semi-tubular self-piercing rivets made of high-strength steel are presented.
ED - Kuball, Clara-Maria
ED - Uhe, Benedikt
ED - Meschut, Gerson
ED - Merklein, Marion
ID - 19976
KW - high nitrogen steel
KW - self-piercing riveting
KW - joining by forming
KW - bulk forming
KW - tool design
TI - Process design for the forming of semi-tubular self-piercing rivets made of high nitrogen steel
VL - 50
ER -
TY - CONF
AB - We consider a natural extension to the metric uncapacitated Facility Location Problem (FLP) in which requests ask for different commodities out of a finite set \( S \) of commodities.
Ravi and Sinha (SODA 2004) introduced the model as the \emph{Multi-Commodity Facility Location Problem} (MFLP) and considered it an offline optimization problem.
The model itself is similar to the FLP: i.e., requests are located at points of a finite metric space and the task of an algorithm is to construct facilities and assign requests to facilities while minimizing the construction cost and the sum over all assignment distances.
In addition, requests and facilities are heterogeneous; they request or offer multiple commodities out of $S$.
A request has to be connected to a set of facilities jointly offering the commodities demanded by it.
In comparison to the FLP, an algorithm has to decide not only if and where to place facilities, but also which commodities to offer at each.
To the best of our knowledge we are the first to study the problem in its online variant in which requests, their positions and their commodities are not known beforehand but revealed over time.
We present results regarding the competitive ratio.
On the one hand, we show that heterogeneity influences the competitive ratio by developing a lower bound on the competitive ratio for any randomized online algorithm of \( \Omega ( \sqrt{|S|} + \frac{\log n}{\log \log n} ) \) that already holds for simple line metrics.
Here, \( n \) is the number of requests.
On the other side, we establish a deterministic \( \mathcal{O}(\sqrt{|S|} \cdot \log n) \)-competitive algorithm and a randomized \( \mathcal{O}(\sqrt{|S|} \cdot \frac{\log n}{\log \log n} ) \)-competitive algorithm.
Further, we show that when considering a more special class of cost functions for the construction cost of a facility, the competitive ratio decreases given by our deterministic algorithm depending on the function.
AU - Castenow, Jannik
AU - Feldkord, Björn
AU - Knollmann, Till
AU - Malatyali, Manuel
AU - Meyer auf der Heide, Friedhelm
ID - 17370
KW - Online Multi-Commodity Facility Location
KW - Competitive Ratio
KW - Online Optimization
KW - Facility Location Problem
SN - 9781450369350
T2 - Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures
TI - The Online Multi-Commodity Facility Location Problem
ER -
TY - JOUR
AU - Otroshi, Mortaza
AU - Rossel, Moritz
AU - Meschut, Gerson
ID - 20143
JF - Journal of Advanced Joining Processes
KW - Self-pierce riveting
KW - Ductile fracture
KW - Damage modeling
KW - GISSMO damage model
TI - Stress state dependent damage modeling of self-pierce riveting process simulation using GISSMO damage model
VL - 1
ER -
TY - JOUR
AB - Im Artikel werden drei verschiedene Lernzugänge (kom-petenzorientiertes, ästhetisches und biographisches Lernen) vorgestellt und aus theoretischer Perspektive deren motivierender Gehalt für selbstreguliertes Lernen in Praxisphasen des Lehramtsstudiumsherausgearbeitet. Als theoretische Grund-lage dient die Selbstbestimmungstheorie als zentrale motivationale Theorie zur Erklärung selbstbestimmten Handelns.
AU - Caruso, Carina
AU - Adammek, Christine
AU - Bonanati, Sabrina
AU - Wiescholek, Sybille
ID - 35298
IS - 1
JF - Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion
KW - ästhetische Forschung
KW - Biographiearbeit
KW - Praxissemester
KW - Professionalisierung
KW - selbstreguliertes Lernen
KW - Motivation / aesthetic research
KW - biographical work
KW - long-term internship
KW - profes-sionalization
KW - self-regulated learning
KW - motivation
SN - 2625-0675
TI - Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen
VL - 3
ER -
TY - JOUR
AB - Helhmoltz–Kirchhoff equations of motions of vortices of an incompressible fluid in the plane define a dynamics with singularities and this leads to a Zermelo navigation problem describing the ship travel in such a field where the control is the heading angle. Considering one vortex, we define a time minimization problem which can be analyzed with the technics of geometric optimal control combined with numerical simulations, the geometric frame being the extension of Randers metrics in the punctured plane, with rotational symmetry. Candidates as minimizers are parameterized thanks to the Pontryagin Maximum Principle as extremal solutions of a Hamiltonian vector field. We analyze the time minimal solution to transfer the ship between two points where during the transfer the ship can be either in a strong current region in the vicinity of the vortex or in a weak current region. The analysis is based on a micro-local classification of the extremals using mainly the integrability properties of the dynamics due to the rotational symmetry. The discussion is complex and related to the existence of an isolated extremal (Reeb) circle due to the vortex singularity. The explicit computation of cut points where the extremal curves cease to be optimal is given and the spheres are described in the case where at the initial point the current is weak.
AU - Bonnard, Bernard
AU - Cots, Olivier
AU - Wembe Moafo, Boris Edgar
ID - 33866
JF - ESAIM: Control, Optimisation and Calculus of Variations
KW - Computational Mathematics
KW - Control and Optimization
KW - Control and Systems Engineering
SN - 1292-8119
TI - A Zermelo navigation problem with a vortex singularity
VL - 27
ER -
TY - GEN
AB - Due to the trend towards lightweight design in car body development mechanical joining technologies become increasingly important. These techniques allow for the joining of dissimilar materials and thus enable multi-material design, while thermic joining methods reach their limits. Semi-tubular self-piercing riveting is an important mechanical joining technology. The rivet production, however, is costly and time-consuming, as the process consists of several process steps including the heat treatment and coating of the rivets in order to achieve an adequate strength and corrosion resistance. The use of high nitrogen steel as rivet material leads to the possibility of reducing process steps and hence increasing the efficiency of the process. However, the high tool loads being expected due to the high strain hardening of the material are a major challenge during the rivet production. Thus, there is a need for appropriate forming strategies, such as the manufacturing of the rivets at elevated temperatures. Prior investigations led to the conclusion that forming already at 200 °C results in a distinct reduction of the yield strength. To create a deeper understanding of the forming behaviour of high nitrogen steel at elevated temperatures, compression tests were conducted in a temperature range between room temperature and 200 °C. The determined true stress – true strain curves are the basis for the further process and tool design of the rivet production. Another key factor for the rivet manufacturing at elevated temperatures is the influence of the process temperature on the tribological conditions. For this reason, ring compression tests at room temperature and 200 °C are carried out. The friction factors are determined on the basis of calibration curves resulting from the numerical analysis of the ring compression process. The investigations indicate that the friction factor at 200 °C is significantly higher compared to room temperature. This essential fact has to be taken into account for the process and tool design for the rivet production using high nitrogen steel.
ED - Kuball, Clara-Maria
ED - Jung, R
ED - Uhe, Benedikt
ED - Meschut, Gerson
ED - Merklein, Marion
ID - 19974
KW - High nitrogen steel
KW - Self-piercing riveting
KW - Joining by forming
KW - Bulk forming
KW - Strain hardening
TI - Influence of the process temperature on the forming behaviour and the friction during bulk forming of high nitrogen steel
VL - 1
ER -
TY - JOUR
AB - As a result of lightweight design, increased use is being made of high-strength steel and aluminium in car bodies. Self-piercing riveting is an established technique for joining these materials. The dissimilar properties of the two materials have led to a number of different rivet geometries in the past. Each rivet geometry fulfils the requirements of the materials within a limited range. In the present investigation, an improved rivet geometry is developed, which permits the reliable joining of two material combinations that could only be joined by two different rivet geometries up until now. Material combination 1 consists of high-strength steel on both sides, while material combination 2 comprises aluminium on the punch side and high-strength steel on the die side. The material flow and the stress and strain conditions prevailing during the joining process are analysed by means of numerical simulation. The rivet geometry is then improved step-by-step on the basis of this analysis. Finally, the improved rivet geometry is manufactured and the findings of the investigation are verified in experimental joining tests.
AU - Uhe, Benedikt
AU - Kuball, Clara-Maria
AU - Merklein, Marion
AU - Meschut, Gerson
ID - 19973
JF - Production Engineering
KW - Self-piercing riveting
KW - Joining technology
KW - Rivet geometry
KW - Multi-material design
KW - High-strength steel
KW - Aluminium
TI - Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints
VL - 14
ER -
TY - JOUR
AB - We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs – both to be minimized – is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers.
AU - Bossek, Jakob
AU - Kerschke, Pascal
AU - Trautmann, Heike
ID - 46334
JF - Applied Soft Computing
KW - Algorithm selection
KW - Multi-objective optimization
KW - Performance measurement
KW - Combinatorial optimization
KW - Traveling Salesperson Problem
SN - 1568-4946
TI - A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms
VL - 88
ER -
TY - CONF
AB - Dynamic optimization problems have gained significant attention in evolutionary computation as evolutionary algorithms (EAs) can easily adapt to changing environments. We show that EAs can solve the graph coloring problem for bipartite graphs more efficiently by using dynamic optimization. In our approach the graph instance is given incrementally such that the EA can reoptimize its coloring when a new edge introduces a conflict. We show that, when edges are inserted in a way that preserves graph connectivity, Randomized Local Search (RLS) efficiently finds a proper 2-coloring for all bipartite graphs. This includes graphs for which RLS and other EAs need exponential expected time in a static optimization scenario. We investigate different ways of building up the graph by popular graph traversals such as breadth-first-search and depth-first-search and analyse the resulting runtime behavior. We further show that offspring populations (e. g. a (1 + {$\lambda$}) RLS) lead to an exponential speedup in {$\lambda$}. Finally, an island model using 3 islands succeeds in an optimal time of {$\Theta$}(m) on every m-edge bipartite graph, outperforming offspring populations. This is the first example where an island model guarantees a speedup that is not bounded in the number of islands.
AU - Bossek, Jakob
AU - Neumann, Frank
AU - Peng, Pan
AU - Sudholt, Dirk
ID - 48847
KW - dynamic optimization
KW - evolutionary algorithms
KW - running time analysis
KW - theory
SN - 978-1-4503-7128-5
T2 - Proceedings of the Genetic and Evolutionary Computation Conference
TI - More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization
ER -
TY - CONF
AB - One-shot optimization tasks require to determine the set of solution candidates prior to their evaluation, i.e., without possibility for adaptive sampling. We consider two variants, classic one-shot optimization (where our aim is to find at least one solution of high quality) and one-shot regression (where the goal is to fit a model that resembles the true problem as well as possible). For both tasks it seems intuitive that well-distributed samples should perform better than uniform or grid-based samples, since they show a better coverage of the decision space. In practice, quasi-random designs such as Latin Hypercube Samples and low-discrepancy point sets are indeed very commonly used designs for one-shot optimization tasks. We study in this work how well low star discrepancy correlates with performance in one-shot optimization. Our results confirm an advantage of low-discrepancy designs, but also indicate the correlation between discrepancy values and overall performance is rather weak. We then demonstrate that commonly used designs may be far from optimal. More precisely, we evolve 24 very specific designs that each achieve good performance on one of our benchmark problems. Interestingly, we find that these specifically designed samples yield surprisingly good performance across the whole benchmark set. Our results therefore give strong indication that significant performance gains over state-of-the-art one-shot sampling techniques are possible, and that evolutionary algorithms can be an efficient means to evolve these.
AU - Bossek, Jakob
AU - Doerr, Carola
AU - Kerschke, Pascal
AU - Neumann, Aneta
AU - Neumann, Frank
ID - 48849
KW - Continuous optimization
KW - Fully parallel search
KW - One-shot optimization
KW - Regression
KW - Surrogate-assisted optimization
SN - 978-3-030-58111-4
T2 - Parallel Problem Solving from Nature (PPSN XVI)
TI - Evolving Sampling Strategies for One-Shot Optimization Tasks
ER -
TY - CONF
AB - Several important optimization problems in the area of vehicle routing can be seen as variants of the classical Traveling Salesperson Problem (TSP). In the area of evolutionary computation, the Traveling Thief Problem (TTP) has gained increasing interest over the last 5 years. In this paper, we investigate the effect of weights on such problems, in the sense that the cost of traveling increases with respect to the weights of nodes already visited during a tour. This provides abstractions of important TSP variants such as the Traveling Thief Problem and time dependent TSP variants, and allows to study precisely the increase in difficulty caused by weight dependence. We provide a 3.59-approximation for this weight dependent version of TSP with metric distances and bounded positive weights. Furthermore, we conduct experimental investigations for simple randomized local search with classical mutation operators and two variants of the state-of-the-art evolutionary algorithm EAX adapted to the weighted TSP. Our results show the impact of the node weights on the position of the nodes in the resulting tour.
AU - Bossek, Jakob
AU - Casel, Katrin
AU - Kerschke, Pascal
AU - Neumann, Frank
ID - 48851
KW - dynamic optimization
KW - evolutionary algorithms
KW - running time analysis
KW - theory
SN - 978-1-4503-7128-5
T2 - Proceedings of the Genetic and Evolutionary Computation Conference
TI - The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics
ER -
TY - CONF
AB - In practice, e.g. in delivery and service scenarios, Vehicle-Routing-Problems (VRPs) often imply repeated decision making on dynamic customer requests. As in classical VRPs, tours have to be planned short while the number of serviced customers has to be maximized at the same time resulting in a multi-objective problem. Beyond that, however, dynamic requests lead to the need for re-planning of not yet realized tour parts, while already realized tour parts are irreversible. In this paper we study this type of bi-objective dynamic VRP including sequential decision making and concurrent realization of decisions. We adopt a recently proposed Dynamic Evolutionary Multi-Objective Algorithm (DEMOA) for a related VRP problem and extend it to the more realistic (here considered) scenario of multiple vehicles. We empirically show that our DEMOA is competitive with a multi-vehicle offline and clairvoyant variant of the proposed DEMOA as well as with the dynamic single-vehicle approach proposed earlier.
AU - Bossek, Jakob
AU - Grimme, Christian
AU - Trautmann, Heike
ID - 48845
KW - decision making
KW - dynamic optimization
KW - evolutionary algorithms
KW - multi-objective optimization
KW - vehicle routing
SN - 978-1-4503-7128-5
T2 - Proceedings of the Genetic and Evolutionary Computation Conference
TI - Dynamic Bi-Objective Routing of Multiple Vehicles
ER -
TY - CONF
AB - Sequential model-based optimization (SMBO) approaches are algorithms for solving problems that require computationally or otherwise expensive function evaluations. The key design principle of SMBO is a substitution of the true objective function by a surrogate, which is used to propose the point(s) to be evaluated next. SMBO algorithms are intrinsically modular, leaving the user with many important design choices. Significant research efforts go into understanding which settings perform best for which type of problems. Most works, however, focus on the choice of the model, the acquisition function, and the strategy used to optimize the latter. The choice of the initial sampling strategy, however, receives much less attention. Not surprisingly, quite diverging recommendations can be found in the literature. We analyze in this work how the size and the distribution of the initial sample influences the overall quality of the efficient global optimization (EGO) algorithm, a well-known SMBO approach. While, overall, small initial budgets using Halton sampling seem preferable, we also observe that the performance landscape is rather unstructured. We furthermore identify several situations in which EGO performs unfavorably against random sampling. Both observations indicate that an adaptive SMBO design could be beneficial, making SMBO an interesting test-bed for automated algorithm design.
AU - Bossek, Jakob
AU - Doerr, Carola
AU - Kerschke, Pascal
ID - 48850
KW - continuous black-box optimization
KW - design of experiments
KW - initial design
KW - sequential model-based optimization
SN - 978-1-4503-7128-5
T2 - Proceedings of the Genetic and Evolutionary Computation Conference
TI - Initial Design Strategies and Their Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB
ER -
TY - JOUR
AB - We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs \textendash both to be minimized \textendash is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers. \textbullet The multi-objective perspective is naturally generalizable to multiple objectives. \textbullet Proof of relationship between HV and the PAR in the considered bi-objective space. \textbullet New insights into complementary behavior of stochastic optimization algorithms.
AU - Bossek, Jakob
AU - Kerschke, Pascal
AU - Trautmann, Heike
ID - 48848
IS - C
JF - Applied Soft Computing
KW - Algorithm selection
KW - Combinatorial optimization
KW - Multi-objective optimization
KW - Performance measurement
KW - Traveling Salesperson Problem
SN - 1568-4946
TI - A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms
VL - 88
ER -
TY - JOUR
AB - Employing main and sector-specific investment-grade CDS indices from the North American and European CDS market and performing mean-variance out-of-sample analyses for conservative and aggressive investors over the period from 2006 to 2014, this paper analyzes portfolio benefits of adding corporate CDS indices to a traditional financial portfolio consisting of stock and sovereign bond indices. As a baseline result, we initially find an increase in portfolio (downside) risk-diversification when adding CDS indices, which is observed irrespective of both CDS markets, investor-types and different sub-periods, including the global financial crisis and European sovereign debt crisis. In addition, the analysis reveals higher portfolio excess returns and performance in CDS index portfolios, however, these effects clearly differ between markets, investor-types and sub-periods. Overall, portfolio benefits of adding CDS indices mainly result from the fact that institutional investors replace sovereign bond indices rather than stock indices by CDS indices due to better risk-return characteristics. Our baseline findings remain robust under a variety of robustness checks. Results from sensitivity analyses provide further important implications for institutional investors with a strategic focus on a long-term conservative portfolio management.
AU - Hippert, Benjamin
AU - Uhde, André
AU - Wengerek, Sascha Tobias
ID - 4562
IS - 2
JF - Review of Derivatives Research
KW - Corporate credit default swap indices
KW - Mean-variance asset allocation
KW - Out-of-sample portfolio optimization
KW - Portfolio risk-diversification
KW - Portfolio performance evaluation
TI - Portfolio Benefits of Adding Corporate Credit Default Swap Indices: Evidence from North America and Europe
VL - 22
ER -
TY - THES
AB - Ultraschall wird zur Effizienzsteigerung in verfahrenstechnischen Prozessen eingesetzt. Die Betriebsparamter der Ultraschallsysteme werden empirisch ermittelt, da derzeit keine systematische Analyse der Wechselwirkung zwischen Ultraschallwandler und Schallfeld sowie kein Verfahren zur Messung der Kavitationsaktivität ohne zusätzlichen Sensor existieren. Auf Basis einer experimentellen Analyse des betrachteten sonochemischen Reaktors wird ein Finite-Elemente-Modell aufgebaut, das die Wechselwirkung zwischen Schallfeld und Ultraschallwandler berücksichtigt. Die modellbasierte Analyse zeigt, dass wegen der akustischen Eigenschaften des Autoklavs nur direkt an der Sonotrode Kavitation entsteht. Die Wechselwirkung zwischen Ultraschallwandler und Schallfeld ermöglicht Aussagen über das Schallfeld und die Kavitationsaktivität auf Basis der Rückwirkung auf den Ultraschallwandler. Die lineare Schalldruckverteilung ermöglicht eine Prognose über die Verteilung von Kavitationszonen. Das beschriebene Modell liefert wertvolle Erkenntnisse für die Auslegung, Analyse und Skalierung sonochemischer Reaktoren. Auf Grund der rauen Prozessrandbedingungen ist die Applikation von Sensoren zur Überwachung der Kavitationsaktivität in vielen sonochemischen Prozessen nicht möglich. Zur prozessbegleitenden Messung der Kavitationsaktivität wird ein Verfahren entwickelt, das die Bewertung der Kavitationsaktivität durch Auswertung der Rückwirkung auf den Ultraschallwandler erlaubt. Das Messverfahren ermöglicht eine vorhersagbare und reproduzierbare Durchführung kavitationsbasierter Prozesse und stellt eine wichtige Erweiterung für bestehende und neue Ultraschallsysteme dar.
AU - Bornmann, Peter
ID - 10000
KW - Sonochemie
KW - Akustische Kavitation
KW - Kavitationsmessung
KW - Kavitationsdetektion
KW - FEM-Simulation Ultraschallwandler
KW - Prozessüberwachung
KW - FEM-Simulation Schallfeld
KW - Self-Sensing
KW - Piezoelektrische Ultraschallwandler
KW - Ultraschallreinigung
TI - Modellierung und experimentelle Charakterisierung der Wechselwirkung zwischen Ultraschallwandler und Flüssigkeit in kavitationsbasierten Prozessen
ER -