摘要
由于模糊关系方程在很多领域有着广泛的应用,越来越多的研究人员加入到求其极小解的工作中去,但结果不是很理想.该文用量子行为粒子群算法(QPSO)来求解其极小解,希望在模糊关系方程解的寻优问题上有所进展.将所提出的QPSO算法求解模糊关系方程的方法与遗传算法(GA)的求解方法作比较,发现QPSO优化算法较GA算法更能有效地找出模糊关系方程的近似最优解.
Because of fuzzy relation equation was applied extensively in many fields, more and more researchers have joined in its minimal solution work. But the result is not perfect. This article tries to use Optimization for solving the minimal solution, hoping to see the progress on the optimization problem of solving fuzzy relation equation. QPSO algorithm is more effective to find the approximate optimal solution than genetic algorithm （GA） by comparing QPSO algorithm with GA algorithm to solve the fuzzy relation equation, which will be presented in this paper.
出处
《广西师范学院学报（自然科学版）》
2015年第2期25-29,共5页
Journal of Guangxi Teachers Education University(Natural Science Edition)
基金
北部湾环境演变与资源利用教育部重点实验室系统基金(2014BGERLXT11)
关键词
量子粒子群优化算法
遗传算法
模糊关系方程
近似最优解
QPSO algorithm
genetic algorithm（GA）
fuzzy relation equation
the approximate optimal solution
