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.