求解物流中心选址问题的猴群算法

doi:10.16182/j.issn1004731x.joss.201806034

系统仿真学报 ›› 2018, Vol. 30 ›› Issue (6): 2272-2278.doi: 10.16182/j.issn1004731x.joss.201806034

求解物流中心选址问题的猴群算法

徐小平, 张东洁

西安理工大学理学院,陕西西安 710054

收稿日期:2016-08-05 修回日期:2017-05-10 出版日期:2018-06-08 发布日期:2018-06-14
作者简介:徐小平(1973-),男,陕西蓝田,博士,教授,研究方向为进化算法,系统建模理论等;张东洁(1990-),女,陕西西安,硕士生,研究方向为系统优化、控制与辨识。
基金资助:
国家自然科学基金(61773016),西安理工大学科技创新计划(2016CX013)

Monkey Algorithm for Solving Logistics Center Location Selection Problem

Xu Xiaoping, Zhang Dongjie

School of Sciences, Xi'an University of Technology, Xi'an 710054, China

Received:2016-08-05 Revised:2017-05-10 Online:2018-06-08 Published:2018-06-14

摘要/Abstract

摘要： 物流中心选址问题是影响物流中心整体建设发展的最基础问题,加强物流中心选址问题研究具有十分重要的意义。然而,它是一个被人们广泛关注的NP问题。因此,本文利用一种改进的猴群算法来求解物流中心选址问题。给出一种改进方法,其基本思想为采用混沌变量产生猴群算法的初始可行解,在爬过程中采用递减的因子作为爬步长以及在望过程中引用混沌搜索法来提高算法性能。利用改进算法求解物流中心选址问题。在仿真实验中,分别利用对典型函数和物流中心选址问题的求解结果说明了所提方法是可行的。

关键词: 物流中心选址, 猴群算法, 混沌变量, 递减的因子, 混沌搜索法

Abstract: The location selection of logistics center is the most basic problem that affects the whole development of logistics center; an improved monkey algorithm is used to solve the problem. The basic idea is that the chaos variables are used to generate the initial feasible solution of the monkey algorithm, the decreasing factor is taken as the climbing step in the climbing process and a chaotic search method is introduced in the looking process to improve the performance of the algorithm. Through simulation experiment, the solution results of typical function and logistics center location problem are given to illustrate the feasibility of the proposed method.

Key words: logistics center location, monkey algorithm, chaotic variables, descending factor, chaotic search method

中图分类号:

TP273+.4A

徐小平, 张东洁. 求解物流中心选址问题的猴群算法[J]. 系统仿真学报, 2018, 30(6): 2272-2278.

Xu Xiaoping, Zhang Dongjie. Monkey Algorithm for Solving Logistics Center Location Selection Problem[J]. Journal of System Simulation, 2018, 30(6): 2272-2278.

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求解物流中心选址问题的猴群算法

Monkey Algorithm for Solving Logistics Center Location Selection Problem

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