Multiobjective particle swarm optimization based on differential evolution for environmental/economic dispatch problem
This paper presents a multiobjective particle swarm optimization based on differential evolution (IMOPSO-DE) algorithm for environmental/economic dispatch (EED) problem. The algorithm adopted differential evolution to increase the diversity of the Pareto set. Circular crowded sorting approach helped to generate a set of well-distributed Pareto-optimal solutions in one run. The global best individuals in multiobjective optimization domain are redefined through a new multiobjective fitness roulette technique. Several optimization runs of the proposed approach have been carried out on the IEEE30-BUS six-generator test system. Simulation results revealed that proposed approach obtained high-quality solutions and was able to provide a satisfactory compromise solution in almost all the trials, thereby validating the efficacy and applicability of the proposed approach over the real-word multiobjective optimization problems.
Environmental/economic dispatch Differential evolution Particle swarm optimization Multiobjective optimization
WU Ya-li XU Li-qing ZHANG Jin
School of Automation and Information Engineering Xi’an University of Technology, shaanxi, China School of Automation and Information Engineering, Xi’an University of Technology, shaanxi, China
国际会议
2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)
四川绵阳
英文
1498-1503
2011-05-23（万方平台首次上网日期，不代表论文的发表时间）