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|a 9783540729600
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|a Siarry, Patrick
|e [editor]
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|a Advances in Metaheuristics for Hard Optimization
|h Elektronische Ressource
|c edited by Patrick Siarry, Zbigniew Michalewicz
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|a 1st ed. 2008
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260 |
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|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 2008, 2008
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|a XVI, 481 p. 167 illus
|b online resource
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|a Comparison of Simulated Annealing, Interval Partitioning and Hybrid Algorithms in Constrained Global Optimization -- Four-bar Mechanism Synthesis for n Desired Path Points Using Simulated Annealing -- “MOSS-II” Tabu/Scatter Search for Nonlinear Multiobjective Optimization -- Feature Selection for Heterogeneous Ensembles of Nearest-neighbour Classifiers Using Hybrid Tabu Search -- A Parallel Ant Colony Optimization Algorithm Based on Crossover Operation -- An Ant-bidding Algorithm for Multistage Flowshop Scheduling Problem: Optimization and Phase Transitions -- Dynamic Load Balancing Using an Ant Colony Approach in Micro-cellular Mobile Communications Systems -- New Ways to Calibrate Evolutionary Algorithms -- Divide-and-Evolve: a Sequential Hybridization Strategy Using Evolutionary Algorithms -- Local Search Based on Genetic Algorithms -- Designing Efficient Evolutionary Algorithms for Cluster Optimization: A Study on Locality -- Aligning Time Series with Genetically Tuned Dynamic Time Warping Algorithm -- Evolutionary Generation of Artificial Creature’s Personality for Ubiquitous Services -- Some Guidelines for Genetic Algorithm Implementation in MINLP Batch Plant Design Problems -- Coevolutionary Genetic Algorithm to Solve Economic Dispatch -- An Evolutionary Approach to Solve a Novel Mechatronic Multiobjective Optimization Problem -- Optimizing Stochastic Functions Using a Genetic Algorithm: An Aeronautic Military Application -- Learning Structure Illuminates Black Boxes – An Introduction to Estimation of Distribution Algorithms -- Making a Difference to Differential Evolution -- Hidden Markov Models Training Using Population-based Metaheuristics -- Inequalities and Target Objectives for Metaheuristic Search – Part I: Mixed Binary Optimization
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|a Operations Research, Management Science
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653 |
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|a Operations research
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|a Optimization
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|a Computer science
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653 |
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|a Management science
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653 |
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|a Engineering design
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653 |
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|a Artificial Intelligence
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653 |
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|a Artificial intelligence
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653 |
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|a Engineering Design
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653 |
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|a Theory of Computation
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653 |
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|a Mathematical optimization
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700 |
1 |
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|a Michalewicz, Zbigniew
|e [editor]
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041 |
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7 |
|a eng
|2 ISO 639-2
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|b Springer
|a Springer eBooks 2005-
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|a Natural Computing Series
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|a 10.1007/978-3-540-72960-0
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|u https://doi.org/10.1007/978-3-540-72960-0?nosfx=y
|x Verlag
|3 Volltext
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|a 519.6
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|a Many advances have been made recently in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general-purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and various metaheuristics. The book gathers contributions related to the following topics: theoretical developments in metaheuristics; adaptation of discrete metaheuristics to continuous optimization; performance comparisons of metaheuristics; cooperative methods combining different approaches; parallel and distributed metaheuristics for multiobjective optimization; software implementations; and real-world applications. This book is suitable for practitioners, researchers and graduate students in disciplines such as optimization, heuristics, operations research, and natural computing
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