Advances in Metaheuristics for Hard Optimization [electronic resource] / edited by Patrick Siarry, Zbigniew Michalewicz.

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 -- ǣMOSS-IIǥ 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 Creatures 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.

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.

ZDB-2-SCS