Particle Swarm OptimizationJohn Wiley & Sons, 5. 1. 2010 - Počet stran: 244 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. |
Obsah
| 13 | |
Introduction | 17 |
Part I Particle Swarm Optimization | 21 |
Part II Outlines | 193 |
Further Information | 231 |
| 233 | |
| 239 | |
Další vydání - Zobrazit všechny
Běžně se vyskytující výrazy a sousloví
according Ackley adaptive Alpine 10D amatheurs average number benchmark set Best local perf best performance better calculated Chapter cmax combinatorial problem confidence coefficients consider convergence coordinates decrease defined differential evolution dimension discrete displacement effective ellipsoids equations of motion estimate evolution example executions explorer fact Figure fixed topology formula function Gaussian genetic algorithms give given graph of information hypersphere improvement increment influence information links initially integer iteration kiss_y least less Let us note local minima local optimum maximum number memory-swarm method minimized modified multicriterion necessary Nevertheless nodes null number of evaluations number of informants obtained optimum Parabola 30D Particle Swarm Particle Swarm Optimization performance maps possible precisely probability pseudo-random random randomly rate of failure Rosenbrock Rosenbrock function search space simple strategy Table theoretical total number traditional PSO traveling salesman problem TRIBES Tripod uniform distribution variable vector velocity