Comparing inertia weights and constriction factors in particle swarm optimization 论文

2002引用 2957
Metaheuristic Optimization Algorithms ResearchEvolutionary Algorithms and ApplicationsAdvanced Multi-Objective Optimization Algorithms

详细信息

发表日期
2002-11-07
发表年份
2002

关键词

Metaheuristic Optimization Algorithms ResearchEvolutionary Algorithms and ApplicationsAdvanced Multi-Objective Optimization Algorithms

摘要

The performance of particle swarm optimization using an inertia weight is compared with performance using a constriction factor. Five benchmark functions are used for the comparison. It is concluded that the best approach is to use the constriction factor while limiting the maximum velocity Vmax to the dynamic range of the variable Xmax on each dimension. This approach provides performance on the benchmark functions superior to any other published results known by the authors.