PSO优化在模糊联合补充问题中的应用

计算机工程与应用 ›› 2012, Vol. 48 ›› Issue (35): 238-242.

PSO优化在模糊联合补充问题中的应用

冯钧，李成严

哈尔滨理工大学计算机科学与技术学院，哈尔滨 150080

出版日期:2012-12-11 发布日期:2012-12-21

PSO-optimization method of joint replenishment problem with fuzzy requirement

FENG Jun, LI Chengyan

School of Computer Science & Engineering, Harbin University of Science and Technology, Harbin 150080, China

Online:2012-12-11 Published:2012-12-21

摘要/Abstract

摘要： 对用PSO算法解决需求为不确定的联合补充问题进行了研究。运用模糊规划方法处理需求为模糊变量的联合补充问题，得到了作为求解目标的模糊数学模型；采用PSO思想对该模型进行分析，转化为PSO问题模型，制定出算法流程，并用数值实例验证了提出的粒子群优化模型和求解算法的有效性；对随机生成的大量数据进行处理，结果证明问题规模相同时该算法较遗传算法具有更高的效率。

关键词: 粒子群优化（PSO）算法, 模糊需求, 联合补充问题

Abstract: The solution to the Joint Replenishment Problem（JRP） with fuzzy resource constraint by PSO algorithm is studied. Fuzzy programming method is used to deal with the joint replenishment problem with fuzzy demands, and the fuzzy mathematical model is got. The model is analyzed by PSO method, and converted into a PSO problem model. The algorithm process is worked out. A numerical example shows the effectiveness of the proposed particle swarm optimization model and the algorithm. Much data randomly generated is processed. The results prove that to solve problems under the same scale, this PSO algorithm has a higher efficiency than genetic algorithm.

Key words: Particle Swarm Optimization（PSO） algorithm, fuzzy requirement, joint replenishment problem

冯钧，李成严. PSO优化在模糊联合补充问题中的应用[J]. 计算机工程与应用, 2012, 48(35): 238-242.

FENG Jun, LI Chengyan. PSO-optimization method of joint replenishment problem with fuzzy requirement[J]. Computer Engineering and Applications, 2012, 48(35): 238-242.

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