دانلود کتاب Advances in Metaheuristics for Hard Optimization

فهرست مطالب :

Cover......Page 1
Front matter......Page 2
1. Comparison of Simulated Annealing, Interval Partitioning and Hybrid Algorithms in Constrained Global Optimization......Page 16
2. Four-bar Mechanism Synthesis for......Page 38
3. “MOSS-II” Tabu/Scatter Search for Nonlinear Multiobjective Optimization......Page 53
4. Feature Selection for Heterogeneous Ensembles of Nearest-neighbour Classifiers Using Hybrid Tabu Search......Page 82
5. A Parallel Ant Colony Optimization Algorithm Based on Crossover Operation......Page 99
6. An Ant-bidding Algorithm for Multistage Flowshop Scheduling Problem: Optimization and Phase Transitions......Page 123
7. Dynamic Load Balancing Using an Ant Colony Approach in Micro-cellular Mobile Communications Systems......Page 149
8. New Ways to Calibrate Evolutionary Algorithms......Page 165
9. Divide-and-Evolve: a Sequential Hybridization Strategy Using Evolutionary Algorithms......Page 190
10. Local Search Based on Genetic Algorithms......Page 210
11. Designing Efficient Evolutionary Algorithms for Cluster Optimization: A Study on Locality......Page 233
12. Aligning Time Series with Genetically Tuned Dynamic Time Warping Algorithm......Page 261
13. Evolutionary Generation of Artificial Creature’s Personality for Ubiquitous Services......Page 272
14. Some Guidelines for Genetic Algorithm Implementation in MINLP Batch Plant Design Problems......Page 302
15. Coevolutionary Genetic Algorithm to Solve Economic Dispatch......Page 325
16. An Evolutionary Approach to Solve a Novel Mechatronic Multiobjective Optimization Problem......Page 336
17. Optimizing Stochastic Functions Using a Genetic Algorithm: An Aeronautic Military Application......Page 359
18. Learning Structure Illuminates Black Boxes – An Introduction to Estimation of Distribution Algorithms......Page 370
19. Making a Difference to Differential Evolution......Page 401
20. Hidden Markov Models Training Using Population-based Metaheuristics......Page 419
21. Inequalities and Target Objectives for Metaheuristic Search – Part I: Mixed Binary Optimization......Page 443
Back matter......Page 479