@inbook{48881,
  abstract     = {{Classic automated algorithm selection (AS) for (combinatorial) optimization problems heavily relies on so-called instance features, i.e., numerical characteristics of the problem at hand ideally extracted with computationally low-demanding routines. For the traveling salesperson problem (TSP) a plethora of features have been suggested. Most of these features are, if at all, only normalized imprecisely raising the issue of feature values being strongly affected by the instance size. Such artifacts may have detrimental effects on algorithm selection models. We propose a normalization for two feature groups which stood out in multiple AS studies on the TSP: (a) features based on a minimum spanning tree (MST) and (b) a k-nearest neighbor graph (NNG) transformation of the input instance. To this end we theoretically derive minimum and maximum values for properties of MSTs and k-NNGs of Euclidean graphs. We analyze the differences in feature space between normalized versions of these features and their unnormalized counterparts. Our empirical investigations on various TSP benchmark sets point out that the feature scaling succeeds in eliminating the effect of the instance size. Eventually, a proof-of-concept AS-study shows promising results: models trained with normalized features tend to outperform those trained with the respective vanilla features.}},
  author       = {{Heins, Jonathan and Bossek, Jakob and Pohl, Janina and Seiler, Moritz and Trautmann, Heike and Kerschke, Pascal}},
  booktitle    = {{Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms}},
  isbn         = {{978-1-4503-8352-3}},
  keywords     = {{automated algorithm selection, graph theory, instance features, normalization, traveling salesperson problem (TSP)}},
  pages        = {{1–15}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{On the Potential of Normalized TSP Features for Automated Algorithm Selection}}},
  year         = {{2021}},
}

@inproceedings{48876,
  abstract     = {{In recent years, Evolutionary Algorithms (EAs) have frequently been adopted to evolve instances for optimization problems that pose difficulties for one algorithm while being rather easy for a competitor and vice versa. Typically, this is achieved by either minimizing or maximizing the performance difference or ratio which serves as the fitness function. Repeating this process is useful to gain insights into strengths/weaknesses of certain algorithms or to build a set of instances with strong performance differences as a foundation for automatic per-instance algorithm selection or configuration. We contribute to this branch of research by proposing fitness-functions to evolve instances that show large performance differences for more than just two algorithms simultaneously. As a proof-of-principle, we evolve instances of the multi-component Traveling Thief Problem (TTP) for three incomplete TTP-solvers. Our results point out that our strategies are promising, but unsurprisingly their success strongly relies on the algorithms’ performance complementarity.}},
  author       = {{Bossek, Jakob and Wagner, Markus}},
  booktitle    = {{Proceedings of the Genetic and Evolutionary Computation Conference Companion}},
  isbn         = {{978-1-4503-8351-6}},
  keywords     = {{evolutionary algorithms, evolving instances, fitness function, instance hardness, traveling thief problem (TTP)}},
  pages        = {{1423–1432}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{Generating Instances with Performance Differences for More than Just Two Algorithms}}},
  doi          = {{10.1145/3449726.3463165}},
  year         = {{2021}},
}

@article{48854,
  abstract     = {{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.}},
  author       = {{Bossek, Jakob and Neumann, Frank and Peng, Pan and Sudholt, Dirk}},
  issn         = {{0178-4617}},
  journal      = {{Algorithmica}},
  keywords     = {{Dynamic optimization, Evolutionary algorithms, Running time analysis}},
  number       = {{10}},
  pages        = {{3148–3179}},
  title        = {{{Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem}}},
  doi          = {{10.1007/s00453-021-00838-3}},
  volume       = {{83}},
  year         = {{2021}},
}

@inproceedings{24101,
  abstract     = {{Arburg Plastic Freeforming (APF) is an additive manufacturing process with which three-dimensional, thermoplastic components can be produced layer by layer. Visual and geometrical properties are a major criterion for characterizing the resulting component quality. The aim of this study was to investigate the influences on visual and geometrical properties of APF components depending on process parameters. Initially the focus was on the analysis of the shrinkage behavior of ABS-M30 (Stratasys). On the basis of the results and an existing procedure by the machine manufacturer, an optimized procedure for determining the scaling factors was developed to counteract the shrinkage. With this procedure a higher dimensional accuracy of the components can be achieved. In addition, it was investigated whether an adaption of the form factor based on a mathematical model depending on the component geometry makes sense. The results were transferred into manufacturing guidelines, which allow the user of the APF-technology to optimize process parameters more efficiently.}},
  author       = {{Moritzer, Elmar and Hecker, Felix and Elsner, Christian Lennart and Hirsch, André}},
  booktitle    = {{Proceedings: 2021 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2021)}},
  editor       = {{Bourell, David}},
  location     = {{Austin, Texas, USA}},
  pages        = {{467--474}},
  title        = {{{Investigations for the Optimization of Visual and Geometrical Properties of Arburg Plastic Freeforming Components}}},
  doi          = {{10.26153/tsw/17567}},
  year         = {{2021}},
}

@article{47564,
  author       = {{Reitze, Arnulf and Grünewald, Marcus and Riese, Julia}},
  issn         = {{0888-5885}},
  journal      = {{Industrial & Engineering Chemistry Research}},
  keywords     = {{Industrial and Manufacturing Engineering, General Chemical Engineering, General Chemistry}},
  number       = {{1}},
  pages        = {{740--746}},
  publisher    = {{American Chemical Society (ACS)}},
  title        = {{{Characterization of Liquid-Phase Distribution in 3D Printed Structured Packings with an Enclosed Column Wall}}},
  doi          = {{10.1021/acs.iecr.1c03931}},
  volume       = {{61}},
  year         = {{2021}},
}

@article{47568,
  author       = {{Bruns, Bastian and Herrmann, Felix and Grünewald, Marcus and Riese, Julia}},
  issn         = {{0888-5885}},
  journal      = {{Industrial & Engineering Chemistry Research}},
  keywords     = {{Industrial and Manufacturing Engineering, General Chemical Engineering, General Chemistry}},
  number       = {{20}},
  pages        = {{7678--7688}},
  publisher    = {{American Chemical Society (ACS)}},
  title        = {{{Dynamic Design Optimization for Flexible Process Equipment}}},
  doi          = {{10.1021/acs.iecr.1c00306}},
  volume       = {{60}},
  year         = {{2021}},
}

@article{47570,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Shortened product life cycles and increased demand for specialized products lead to more challenges in efficiently satisfying customer needs. Customer demands are increasingly uncertain in terms of type, location, and volume. As a result, more flexible chemical production plants are required. Modular small‐scale plants can be installed in transportation containers and, therefore, offer the flexibility of easy relocation, enabling production close to the customer or supplier. In a mathematical optimization model, the economic benefit of small‐scale plants in the specialty chemicals market of polymer production is analyzed. Different scenarios created from the real data of a chemical company show that the use of small‐scale plants may lead to a significant reduction in total costs that is mainly due to the transportation costs of raw materials and products.</jats:p>}},
  author       = {{Bruns, Bastian and Becker, Tristan and Riese, Julia and Lier, Stefan and Werners, Brigitte}},
  issn         = {{0930-7516}},
  journal      = {{Chemical Engineering &amp; Technology}},
  keywords     = {{Industrial and Manufacturing Engineering, General Chemical Engineering, General Chemistry}},
  number       = {{6}},
  pages        = {{1148--1152}},
  publisher    = {{Wiley}},
  title        = {{{Efficient Production of Specialized Polymers with Highly Flexible Small‐Scale Plants}}},
  doi          = {{10.1002/ceat.202000591}},
  volume       = {{44}},
  year         = {{2021}},
}

@inproceedings{30693,
  author       = {{Grabo, Matti and Kuckuck, Lennart and Kenig, Eugeny}},
  location     = {{Dubrovnik}},
  title        = {{{Optimization of packed bed latent heat storages filled with PCM-capsules based on super-ellipsoids}}},
  year         = {{2021}},
}

@phdthesis{52665,
  author       = {{Hillebrand, Michael}},
  isbn         = {{978-3-947647-22-4}},
  title        = {{{Entwicklungssystematik zur Integration von Eigenschaften der Selbstheilung in Intelligente Technische Systeme }}},
  volume       = {{Band 403}},
  year         = {{2021}},
}

@article{35744,
  author       = {{Biehler, Rolf and Weigand, Hans-Georg}},
  journal      = {{mathematik lehren}},
  number       = {{228}},
  pages        = {{2–5}},
  publisher    = {{Friedrich Verlag}},
  title        = {{{3D-Geometrie–virtuell und real}}},
  volume       = {{2021}},
  year         = {{2021}},
}

@article{35761,
  author       = {{Höper, Lukas and Malin, Leah and Biehler, Rolf}},
  journal      = {{mathematik lehren}},
  number       = {{228}},
  pages        = {{19–22}},
  publisher    = {{Friedrich Verlag}},
  title        = {{{Schatten von 3D-Objekten: Modellierung mit GeoGebra 3D und Anwendungen in der Computergrafik}}},
  volume       = {{2021}},
  year         = {{2021}},
}

@article{35763,
  author       = {{Hüsing, Sven and Weiser, Niklas and Biehler, Rolf}},
  journal      = {{mathematik lehren}},
  number       = {{228}},
  pages        = {{23–27}},
  publisher    = {{Friedrich Verlag}},
  title        = {{{Faszination 3D-Film: Entwicklung einer 3D-Konstruktion}}},
  volume       = {{2021}},
  year         = {{2021}},
}

@article{53874,
  author       = {{Rastegar, Mehdi and Tavana, Madjid and Meraj, Afshin and Mina, Hassan}},
  issn         = {{0264-410X}},
  journal      = {{Vaccine}},
  number       = {{3}},
  pages        = {{495--504}},
  publisher    = {{Elsevier BV}},
  title        = {{{An inventory-location optimization model for equitable influenza vaccine distribution in developing countries during the COVID-19 pandemic}}},
  doi          = {{10.1016/j.vaccine.2020.12.022}},
  volume       = {{39}},
  year         = {{2021}},
}

@article{53880,
  author       = {{Zare, Habib and Kamali Saraji, Mahyar and Tavana, Madjid and Streimikiene, Dalia and Cavallaro, Fausto}},
  issn         = {{2071-1050}},
  journal      = {{Sustainability}},
  number       = {{22}},
  publisher    = {{MDPI AG}},
  title        = {{{An Integrated Fuzzy Goal Programming—Theory of Constraints Model for Production Planning and Optimization}}},
  doi          = {{10.3390/su132212728}},
  volume       = {{13}},
  year         = {{2021}},
}

@article{53875,
  author       = {{Gheisariha, Elmira and Tavana, Madjid and Jolai, Fariborz and Rabiee, Meysam}},
  issn         = {{0378-4754}},
  journal      = {{Mathematics and Computers in Simulation}},
  pages        = {{152--178}},
  publisher    = {{Elsevier BV}},
  title        = {{{A simulation–optimization model for solving flexible flow shop scheduling problems with rework and transportation}}},
  doi          = {{10.1016/j.matcom.2020.08.019}},
  volume       = {{180}},
  year         = {{2021}},
}

@article{27508,
  abstract     = {{<jats:p>To analyze the influence of suspension kinematics on tire wear, detailed simulation models are required. In this study, a non-linear, flexible multibody model of a rear axle system is built up in the simulation software MSC Adams/View. The physical model comprises the suspension kinematics, compliance, and dynamics as well as the non-linear behavior of the tire using the FTire model. FTire is chosen because it has a separate tire tread model to compute the contact pressure and friction force distribution in the tire contact patch. To build up the simulation model, a large amount of data is needed. Bushings, spring, and damper characteristics are modeled based on measurements. For the structural components (e.g., control arms), reverse engineering techniques are used. The components are 3D-scanned, reworked, and included as a modal reduced finite element (FE)-model using component mode synthesis by Craig–Bampton. Finally, the suspension model is validated by comparing the simulated kinematic and compliance characteristics to experimental results. To investigate the interaction of suspension kinematics and tire wear, straight line driving events, such as acceleration, driving with constant velocity, and deceleration, are simulated with different setups of wheel suspension kinematics. The influence of the setups on the resulting friction work between tire and road is examined, and an exemplarily calculation of tire wear based on a validated FTire tire model is carried out. The results demonstrate, on the one hand, that the chosen concept of elasto-kinematic axle leads to a relatively good match with experimental results and, on the other hand, that there are significant possibilities to reduce tire wear by adjusting the suspension kinematics.</jats:p>}},
  author       = {{Schütte, Jan and Sextro, Walter}},
  issn         = {{2624-8921}},
  journal      = {{Vehicles}},
  pages        = {{233--256}},
  title        = {{{Tire Wear Reduction Based on an Extended Multibody Rear Axle Model}}},
  doi          = {{10.3390/vehicles3020015}},
  year         = {{2021}},
}

@article{45844,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>Abductive reasoning is a non-monotonic formalism stemming from the work of Peirce. It describes the process of deriving the most plausible explanations of known facts. Considering the positive version, asking for sets of variables as explanations, we study, besides the problem of wether there exists a set of explanations, two explanation size limited variants of this reasoning problem (less than or equal to, and equal to a given size bound). In this paper, we present a thorough two-dimensional classification of these problems: the first dimension is regarding the parameterized complexity under a wealth of different parameterizations, and the second dimension spans through all possible Boolean fragments of these problems in Schaefer’s constraint satisfaction framework with co-clones (T. J. Schaefer. The complexity of satisfiability problems. In Proceedings of the 10th Annual ACM Symposium on Theory of Computing, May 1–3, 1978, San Diego, California, USA, R.J. Lipton, W.A. Burkhard, W.J. Savitch, E.P. Friedman, A.V. Aho eds, pp. 216–226. ACM, 1978). Thereby, we almost complete the parameterized complexity classification program initiated by Fellows et al. (The parameterized complexity of abduction. In Proceedings of the Twenty-Sixth AAAI Conference on Articial Intelligence, July 22–26, 2012, Toronto, Ontario, Canada, J. Homann, B. Selman eds. AAAI Press, 2012), partially building on the results by Nordh and Zanuttini (What makes propositional abduction tractable. Artificial Intelligence, 172, 1245–1284, 2008). In this process, we outline a fine-grained analysis of the inherent parameterized intractability of these problems and pinpoint their FPT parts. As the standard algebraic approach is not applicable to our problems, we develop an alternative method that makes the algebraic tools partially available again.</jats:p>}},
  author       = {{Mahmood, Yasir and Meier, Arne and Schmidt, Johannes}},
  issn         = {{0955-792X}},
  journal      = {{Journal of Logic and Computation}},
  keywords     = {{Logic, Hardware and Architecture, Arts and Humanities (miscellaneous), Software, Theoretical Computer Science}},
  number       = {{1}},
  pages        = {{266--296}},
  publisher    = {{Oxford University Press (OUP)}},
  title        = {{{Parameterized complexity of abduction in Schaefer’s framework}}},
  doi          = {{10.1093/logcom/exaa079}},
  volume       = {{31}},
  year         = {{2021}},
}

@inproceedings{46315,
  abstract     = {{We propose a novel method for automated algorithm selection in the domain of single-objective continuous black-box optimization. In contrast to existing methods, we use convolutional neural networks as the selection apparatus which bases its decision on a so-called ‘fitness map’. This fitness map is a 2D representation of a two dimensional search space where different gray scales indicate the quality of found solutions in certain areas. Our devised approach uses a modular CMA-ES framework which offers the option to create the conventional CMA-ES, CMA-ES with the alternate step-size adaptation and many other variants proposed over the years. In total, 4 608 different configurations are possible where most configurations are of complementary nature. In this proof-of-concept work, we consider a subset of 32 possible configurations. The developed method is evaluated against an excerpt of BBOB functions and its performance is compared against baselines that are commonly used in automated algorithm selection - the best standalone algorithm (configuration) and the best obtainable sequence of configurations. While the results indicate that the use of the fitness map is not superior on every benchmark problem, it indubitably shows its merit on more hard-to-solve problems. This offers a promising perspective for generalizing to other types of optimization problems and problem domains.}},
  author       = {{Prager, Raphael Patrick and Seiler, Moritz and Trautmann, Heike and Kerschke, Pascal}},
  booktitle    = {{2021 IEEE Symposium Series on Computational Intelligence (SSCI)}},
  pages        = {{1--8}},
  title        = {{{Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization}}},
  doi          = {{10.1109/SSCI50451.2021.9660174}},
  year         = {{2021}},
}

@inproceedings{46313,
  abstract     = {{Classic automated algorithm selection (AS) for (combinatorial) optimization problems heavily relies on so-called instance features, i.e., numerical characteristics of the problem at hand ideally extracted with computationally low-demanding routines. For the traveling salesperson problem (TSP) a plethora of features have been suggested. Most of these features are, if at all, only normalized imprecisely raising the issue of feature values being strongly affected by the instance size. Such artifacts may have detrimental effects on algorithm selection models. We propose a normalization for two feature groups which stood out in multiple AS studies on the TSP: (a) features based on a minimum spanning tree (MST) and (b) a k-nearest neighbor graph (NNG) transformation of the input instance. To this end we theoretically derive minimum and maximum values for properties of MSTs and k-NNGs of Euclidean graphs. We analyze the differences in feature space between normalized versions of these features and their unnormalized counterparts. Our empirical investigations on various TSP benchmark sets point out that the feature scaling succeeds in eliminating the effect of the instance size. Eventually, a proof-of-concept AS-study shows promising results: models trained with normalized features tend to outperform those trained with the respective vanilla features.}},
  author       = {{Heins, Jonathan and Bossek, Jakob and Pohl, Janina and Seiler, Moritz and Trautmann, Heike and Kerschke, Pascal}},
  booktitle    = {{Proceedings of the 16$^th$ ACM/SIGEVO Conference on Foundations of genetic Algorithms (FOGA XVI)}},
  editor       = {{Computing Machinery Association, for}},
  pages        = {{1–15}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{On the Potential of Normalized TSP Features for Automated Algorithm Selection}}},
  doi          = {{10.1145/3450218.3477308}},
  year         = {{2021}},
}

@inproceedings{36845,
  author       = {{Kruse, Anne and Ott, Manuel and Risse, Lena and Koch, Rainer}},
  location     = {{Berlin}},
  publisher    = {{Deutscher Verband für Materialforschung und -prüfung e.V.}},
  title        = {{{3D-Druck - Eine Technologie als Schlüssel zur Steigerung der Teilhabe}}},
  doi          = {{10.48447/Add-2021-016}},
  year         = {{2021}},
}