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Reflects the advances 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
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.
Content Level »Research
Keywords »Hidden Markov Model - algorithms - data mining - evolutionary algorithm - genetic algorithms - global optimization - heuristics - learning - linear optimization - metaheuristic - multi-objective optimization - nonlinear optimization - operations research - optimization - scheduling