Cantitate/Preț
Produs

Advances in Metaheuristics for Hard Optimization: Natural Computing Series

Editat de Patrick Siarry, Zbigniew Michalewicz
en Limba Engleză Paperback – 22 noi 2010
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.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 91709 lei  43-57 zile
  Springer Berlin, Heidelberg – 22 noi 2010 91709 lei  43-57 zile
Hardback (1) 92432 lei  43-57 zile
  Springer – 19 noi 2007 92432 lei  43-57 zile

Din seria Natural Computing Series

Preț: 91709 lei

Preț vechi: 111840 lei
-18% Nou

Puncte Express: 1376

Preț estimativ în valută:
16226 18903$ 14169£

Carte tipărită la comandă

Livrare economică 19 ianuarie-02 februarie 26

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783642092060
ISBN-10: 3642092063
Pagini: 500
Ilustrații: XVI, 481 p. 167 illus.
Dimensiuni: 155 x 235 x 26 mm
Greutate: 0.69 kg
Ediția:Softcover reprint of hardcover 1st ed. 2008
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Natural Computing Series

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

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.

Textul de pe ultima copertă

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.

Caracteristici

Includes supplementary material: sn.pub/extras