This is the first book devoted entirely to Particle Swarm
Optimization (PSO), which is a non-specific algorithm, similar to
evolutionary algorithms, such as taboo search and ant colonies.
Since its original development in 1995, PSO has mainly been
applied to continuous-discrete heterogeneous strongly non-linear
numerical optimization and it is thus used almost everywhere in the
world. Its convergence rate also makes it a preferred tool in
dynamic optimization.
Table des matières
Foreword.
Introduction.
Part 1: Particle Swarm Optimization.
Chapter 1. What is a difficult problem?
Chapter 2. On a table corner.
Chapter 3. First formulations.
Chapter 4. Benchmark set.
Chapter 5. Mistrusting chance.
Chapter 6. First results.
Chapter 7. Swarm: memory and influence graphs.
Chapter 8. Distributions of proximity.
Chapter 9. Optimal parameter settings.
Chapter 10. Adaptations.
Chapter 11. TRIBES or co-operation of tribes.
Chapter 12. On the constraints.
Chapter 13. Problems and applications.
Chapter 14. Conclusion.
Part 2: Outlines.
Chapter 15. On parallelism.
Chapter 16. Combinatorial problems.
Chapter 17. Dynamics of a swarm.
Chapter 18. Techniques and alternatives.
Further Information.
Bibliography.
Index.
A propos de l’auteur
Maurice Clerc is recognized as one of the foremost PSO specialists in the world. A former France Telecom Research and Development engineer, he maintains his research activities as a consultant for the XPS (e Xtended Particle Swarm) project.
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