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. Particle Swarm Optimization explains the basic principles of the subject, particularly the concepts of particles, information link, memory and cooperation. Starting from a simple but efficient parametric version coded in a few lines, it shows how this can be gradually enhanced to lead to a fully adaptive version. All source programs are either included in the book or are downloadable for free.
Part 1. Particle Swarm Optimization
1. What is a Difficult Problem?
2. On a Table Corner.
3. First Formulations.
4. Benchmark Set.
5. Mistrusting Chance.
6. First Results.
7. Swarm: Memory and Influence Graphs.
8. Distributions of Proximity.
9. Optimal Parameter Settings.
11. TRIBES or Co-operation of Tribes.
12. On the Constraints.
13. Problems and Applications.
Part 2. Outlines
15. On Parallelism.
16. Combinatorial Problems.
17. Dynamics of a Swarm.
18. Techniques and Alternatives.
Maurice Clerc is recognized as one of the foremost PSO specialists in the world. A former France Telecom Research & Development engineer, he maintains his research activities as a consultant for the XPS (eXtended Particle Swarm) project.