西安理工大学学报2011，Vol.27Issue(1)：62-68,7.
求解环境经济调度问题的多目标差分粒子群优化算法
Multiobjective Particle Swarm Optimization Based on Differential Evolution for Environmental/Economic Dispatch Problem
摘要
Abstract
An improved multiobjective particle swarm optimization based on differential evolution technique is proposed for environmental/economic dispatch (EED) problem. The algorithm adopts differential evolution to increase the diversity of the Pareto set. Circular crowded sorting approach helps to generate a set of well-distributed Pareto-optimal solutions in one nm. The global best individuals in multiobjective optimization domain are redefined through a new multiobjective fitness roulette technique. And the adaptire inertia weight and acceleration coefficients enhance the global exploratory capability. The environmental/economic loading distribution model in power system is simulated and compared with other algorithms in references. The results indicate that the improved algorithm can maintain the diversity of Paretooptimal solutions and is of better convergency at the same time.关键词
多目标优化/环境经济调度/差分演化/粒子群优化算法/循环拥挤排序分类
信息技术与安全科学引用本文复制引用
徐丽青,吴亚丽..求解环境经济调度问题的多目标差分粒子群优化算法[J].西安理工大学学报,2011,27(1):62-68,7.基金项目
国家自然科学基金资助项目(60804040) （60804040）
陕西省自然科学基金资助项目(2010JQ8006) （2010JQ8006）
陕西省教育厅科学研究专项基金资助项目(2010JK711). （2010JK711）
