Particle Swarm Optimization

Particles, information link, memory, and cooperation are discussed in this introduction to particle swarm optimization. Starting with a simple but efficient parametric version, this manual shows how to adapt the basic principles for an enhanced, fully adaptive version. All source programs are either included or available for free download. 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, memor Focuses on PSO, a non-specific algorithm inspired by the social behaviour of flocks of birds or shoals of fish. A PSO system combines local and global search methods, attempting to balance exploration with exploitation. This book includes various such source programs