PSO Solution for Linear Programming with Fuzzy Relation Constraints
An optimization model with a linear objective function subject to a system of fuzzy relation equations was presented. Since the non-empty feasible solution set of the fuzzy relation equations was generally a non-convex set, a particle swarm optimization (PSO) algorithm was proposed. The PSO algorithm didnt more complex by the rising of degree of the problem, and could avoid being trapped in local optimum due to using alterable inertia weight. We applied the proposed algorithm to an example, and compared its result with those generated by GA algorithms. The experimental comparison demonstrates that the performance of PSO algorithm is competitive with others and will be an effective method.
particle swarm optimization fuzzy relations linear programming
Xiaojun Wu
Finance/Packaging Engineering of Zhuhai College Jinan University Zhuhai, China
国际会议
北京
英文
440-443
2010-09-18（万方平台首次上网日期，不代表论文的发表时间）