@inproceedings{46396, abstract = {{The steady supply of new optimization methods makes the algorithm selection problem (ASP) an increasingly pressing and challenging task, specially for real-world black-box optimization problems. The introduced approach considers the ASP as a cost-sensitive classification task which is based on Exploratory Landscape Analysis. Low-level features gathered by systematic sampling of the function on the feasible set are used to predict a well-performing algorithm out of a given portfolio. Example-specific label costs are defined by the expected runtime of each candidate algorithm. We use one-sided support vector regression to solve this learning problem. The approach is illustrated by means of the optimization problems and algorithms of the BBOB’09/10 workshop.}}, author = {{Bischl, Bernd and Mersmann, Olaf and Trautmann, Heike and Preuß, Mike}}, booktitle = {{Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation}}, isbn = {{9781450311779}}, keywords = {{machine learning, exploratory landscape analysis, fitness landscape, benchmarking, evolutionary optimization, bbob test set, algorithm selection}}, pages = {{313–320}}, publisher = {{Association for Computing Machinery}}, title = {{{Algorithm Selection Based on Exploratory Landscape Analysis and Cost-Sensitive Learning}}}, doi = {{10.1145/2330163.2330209}}, year = {{2012}}, } @inproceedings{46401, abstract = {{Exploratory Landscape Analysis subsumes a number of techniques employed to obtain knowledge about the properties of an unknown optimization problem, especially insofar as these properties are important for the performance of optimization algorithms. Where in a first attempt, one could rely on high-level features designed by experts, we approach the problem from a different angle here, namely by using relatively cheap low-level computer generated features. Interestingly, very few features are needed to separate the BBOB problem groups and also for relating a problem to high-level, expert designed features, paving the way for automatic algorithm selection.}}, author = {{Mersmann, Olaf and Bischl, Bernd and Trautmann, Heike and Preuss, Mike and Weihs, Claus and Rudolph, Günter}}, booktitle = {{Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation}}, isbn = {{9781450305570}}, keywords = {{exploratory landscape analysis, evolutionary optimization, fitness landscape, benchmarking, BBOB test set}}, pages = {{829–836}}, publisher = {{Association for Computing Machinery}}, title = {{{Exploratory Landscape Analysis}}}, doi = {{10.1145/2001576.2001690}}, year = {{2011}}, } @inproceedings{23858, abstract = {{A large proportion of plastics today is compounded, which means the process from refining a raw material to the processable material. For this process compounding extruders are used which mostly involve tightly intermeshing, co-rotating twin screw extruders. These extruders consist of two closely spaced screws which rotate in the same direction and convey the raw material to the screw tip. These screws are surrounded by several barrel modules which heat or cool the material. As the whole design of the machine is modularly arranged the process behavior of a twin screw extruder depends for the main part on the arrangement of the screw and the barrel elements. Until today this arrangement and process optimization is conducted by experienced engineers and with the help of trial-and-error methods. Furthermore, theoretical models are used with which the behavior of the extruder is estimated. As these models are mostly very complex they are only made available with the realization in different software projects. One of the tools is called SIGMA. Within this paper SIGMA is introduced as a software to optimize a twin screw extruder. SIGMA supports the engineer already in the early stages of the extruder arrangement.}}, author = {{Kretzschmar, Nils and Schöppner, Volker}}, booktitle = {{Proceedings of the 2010 Summer Computer Simulation Conference}}, keywords = {{process optimization, polymer engineering, compounding, twin screw extruder, simulation}}, pages = {{133–140}}, publisher = {{Society for Computer Simulation International}}, title = {{{Simulating Tightly Intermeshing, Co-Rotating Twin Screw Extruders with SIGMA}}}, year = {{2010}}, } @inproceedings{5685, abstract = {{In double-sided markets for computing resources an optimal allocation schedule among job offers and requests subject to relevant capacity constraints can be determined. With increasing storage demands and emerging storage services the question how to schedule storage jobs becomes more and more interesting. Since such scheduling problems are often in the class NP-complete an exact computation is not feasible in practice. On the other hand an approximation to the optimal solution can easily be found by means of using heuristics. The problem with this attempt is that the suggested solution may not be exactly optimal and is thus less satisfying. Considering the two above mentioned solution approaches one can clearly find a trade-off between the optimality of the solution and the efficiency to get to a solution at all. This work proposes to apply and combine heuristics in optimization to gain from both of their benefits while reducing the problematic aspects. Following this method it is assumed to get closer to the optimal solution in a shorter time compared to a full optimization.}}, author = {{Finkbeiner, Josef and Bodenstein, Christian and Schryen, Guido and Neumann, Dirk}}, booktitle = {{18th European Conference on Information Systems (ECIS 2010)}}, keywords = {{Decision Support System, Algorithms, Optimization, Market Engineering}}, title = {{{Applying heuristic methods for job scheduling in storage markets}}}, year = {{2010}}, } @inproceedings{46405, abstract = {{We present methods to answer two basic questions that arise when benchmarking optimization algorithms. The first one is: which algorithm is the ’best’ one? and the second one: which algorithm should I use for my real world problem? Both are connected and neither is easy to answer. We present methods which can be used to analyse the raw data of a benchmark experiment and derive some insight regarding the answers to these questions. We employ the presented methods to analyse the BBOB’09 benchmark results and present some initial findings.}}, author = {{Mersmann, Olaf and Preuss, Mike and Trautmann, Heike}}, booktitle = {{Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I}}, isbn = {{3642158439}}, keywords = {{benchmarking, multidimensional scaling, consensus ranking, evolutionary optimization, BBOB test set}}, pages = {{73–82}}, publisher = {{Springer-Verlag}}, title = {{{Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis}}}, year = {{2010}}, } @inproceedings{9742, abstract = {{New mechatronic systems, called self-optimizing systems, are able to adapt their behavior according to environmental, user and system specific influences. Self-optimizing systems are complex and due to their non-deterministic behavior comprise hidden risks, which cannot be foreseen in the design phase of the system. Therefore, this paper presents modifications of the current condition monitoring policy, to be able to cope with this new kind of systems. Beside avoiding critical situations evoked by self-optimization, the proposed concept uses self-optimization to increase the dependability of the system. In this case, the concept is applied to the active guidance module of an innovative rail-bound vehicle.}}, author = {{Sondermann-Wölke, Christoph and Sextro, Walter}}, booktitle = {{Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns, 2009. COMPUTATIONWORLD '09. Computation World:}}, keywords = {{condition monitoring, mechatronic systems, rail bound vehicle, rail guidance module, self-optimization, self-optimizing function modules, condition monitoring, mechatronics, railway rolling stock, self-adjusting systems}}, pages = {{15 --20}}, title = {{{Towards the Integration of Condition Monitoring in Self-Optimizing Function Modules}}}, doi = {{10.1109/ComputationWorld.2009.47}}, year = {{2009}}, } @article{64041, abstract = {{Three cis-dioxovanadium(V) complexes with similar N -salicylidenehydrazide ligands modeling hydrogen bonding interactions of vanadate relevant for vanadium haloperoxidases are studied by 51V solid-state NMR spectroscopy. Their parameters describing the quadrupolar and chemical shift anisotropy interactions (quadrupolar coupling constant C Q , asymmetry of the quadrupolar tensor η Q , isotropic chemical shift δ iso , chemical shift anisotropy δ σ , asymmetry of the chemical shift tensor η σ and the Euler angles α , β and γ ) are determined both experimentally and theoretically using DFT methods. A comparative study of different methods to determine the NMR parameters by numerical simulation of the spectra is presented. Detailed theoretical investigations on the DFT level using various basis sets and structural models show that by useful choice of the methodology, the calculated parameters agree to the experimental ones in a very good manner.}}, author = {{Schweitzer, Annika and Gutmann, Torsten and Wächtler, Maria and Breitzke, Hergen and Buchholz, Axel and Plass, Winfried and Buntkowsky, Gerd}}, journal = {{Solid State Nuclear Magnetic Resonance}}, keywords = {{51V NMR, Model system, Ab initio calculation, Cis-dioxovanadium(V) complex, Haloperoxidase, Numerical optimization, Quadrupolar interaction}}, number = {{1–2}}, pages = {{52–67}}, title = {{{51V solid-state NMR investigations and DFT studies of model compounds for vanadium haloperoxidases}}}, doi = {{10.1016/j.ssnmr.2008.02.003}}, volume = {{34}}, year = {{2008}}, } @inproceedings{6508, abstract = {{In this paper, we present a framework that supports experimenting with evolutionary hardware design. We describe the framework's modules for composing evolutionary optimizers and for setting up, controlling, and analyzing experiments. Two case studies demonstrate the usefulness of the framework: evolution of hash functions and evolution based on pre-engineered circuits.}}, author = {{Kaufmann, Paul and Platzner, Marco}}, booktitle = {{Second NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2007)}}, isbn = {{076952866X}}, keywords = {{integrated circuit design, hardware evolution, evolutionary hardware design, evolutionary optimizers, hash functions, preengineered circuits, Hardware, Circuits, Design optimization, Visualization, Genetic programming, Genetic mutations, Clustering algorithms, Biological cells, Field programmable gate arrays, Routing}}, location = {{Edinburgh, UK}}, pages = {{447--454}}, publisher = {{IEEE}}, title = {{{MOVES: A Modular Framework for Hardware Evolution}}}, doi = {{10.1109/ahs.2007.73}}, year = {{2007}}, } @inproceedings{11930, abstract = {{For human-machine interfaces in distant-talking environments multichannel signal processing is often employed to obtain an enhanced signal for subsequent processing. In this paper we propose a novel adaptation algorithm for a filter-and-sum beamformer to adjust the coefficients of FIR filters to changing acoustic room impulses, e.g. due to speaker movement. A deterministic and a stochastic gradient ascent algorithm are derived from a constrained optimization problem, which iteratively estimates the eigenvector corresponding to the largest eigenvalue of the cross power spectral density of the microphone signals. The method does not require an explicit estimation of the speaker location. The experimental results show fast adaptation and excellent robustness of the proposed algorithm.}}, author = {{Warsitz, Ernst and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)}}, keywords = {{acoustic filter-and-sum beamforming, acoustic room impulses, acoustic signal processing, adaptive principal component analysis, adaptive signal processing, architectural acoustics, constrained optimization problem, cross power spectral density, deterministic algorithm, deterministic algorithms, distant-talking environments, eigenvalues and eigenfunctions, eigenvector, enhanced signal, filter-and-sum beamformer, FIR filter coefficients, FIR filter coefficients, FIR filters, gradient methods, human-machine interfaces, iterative estimation, iterative methods, largest eigenvalue, microphone signals, multichannel signal processing, optimisation, principal component analysis, spectral analysis, stochastic gradient ascent algorithm, stochastic processes}}, pages = {{iv/797--iv/800 Vol. 4}}, title = {{{Acoustic filter-and-sum beamforming by adaptive principal component analysis}}}, doi = {{10.1109/ICASSP.2005.1416129}}, volume = {{4}}, year = {{2005}}, } @inproceedings{39078, author = {{Gausemeier, Jürgen and Müller, Wolfgang and Paelke, Volker and Bauch, Jürgen and Shen, Q. and Radkowski, R. }}, booktitle = {{Proceedings of the Design 2004}}, keywords = {{mechatronic systems, self-optimization, virtual prototyping}}, location = {{Dubrovnik}}, title = {{{Virtual Prototyping Of Self-Optimizing Mechatronic Systems}}}, year = {{2004}}, }