Title :
Improved Particle Swarm Optimization for Constrained Optimization
Author :
Zhicheng Qu ; Qingyan Li ; Lei Yue
Author_Institution :
Tourism Coll., Sichuan Agric. Univ., Dujiangyan, China
Abstract :
In this paper, we present an improved particle swarm optimization (PSO) algoritlim to solve constrained optimization problems. The proposed approach, called MPSO, employs a novel mutation operator to enhance the global search ability of PSO. In order to deal with constrains, MPSO uses mean violations mechanism and boundaries search. Simulation results on five famous benchmark problems show that MPSO achieves better results than standard PSO and another variant of PSO.
Keywords :
constraint theory; particle swarm optimisation; search problems; MPSO; PSO algorithm; boundary search; constrained optimization problems; global search ability; improved particle swarm optimization algorithm; mean violation mechanism; mutation operator; Benchmark testing; Educational institutions; Optimization; Particle swarm optimization; Sociology; Standards; Statistics; constranined optimization; evolutionary computation; particle swarm optimization (PSO);
Conference_Titel :
Information Technology and Applications (ITA), 2013 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-2876-7
DOI :
10.1109/ITA.2013.64