计算机工程与应用2020，Vol.56Issue(1)：150-157,8.DOI:10.3778/j.issn.1002-8331.1904-0445
求解物流配送中心选址问题的蜘蛛猴算法
Spider Monkey Optimization Algorithm for Solving Location Problem of Logistics Distribution Center
摘要
Abstract
The main idea of the logistics distribution center location problem is to maximize efficiency and minimize costs. In order to quickly obtain a reasonable logistics distribution center location scheme, this paper proposes a quasi-opposition learning spider monkey optimization algorithm based on Laplace distribution(LOBSMO)to solve this problem. Firstly, the model of logistics distribution center location is established. Then, in the basic spider monkey optimization algorithm, the Laplace distribution is used to initialize the swarm of spider monkeys. It uses the exponential decreasing and stochastic logarithmic decreasing strategy to improve the step factor in the local leader phase. In the global leader phase, a new search mechanism and a quasi-opposite learning strategy in the local leader decision phase are adopted to improve the performance of the algorithm. Finally, simulation results show that the proposed method is feasible.关键词
物流配送中心/蜘蛛猴优化算法/Laplace分布/伪反向学习/非线性策略Key words
logistics distribution center/spider monkey optimization algorithm/Laplace distribution/quasi-opposite learning/nonlinear strategy分类
信息技术与安全科学引用本文复制引用
徐小平,杨转,刘龙..求解物流配送中心选址问题的蜘蛛猴算法[J].计算机工程与应用,2020,56(1):150-157,8.基金项目
国家自然科学基金(No.61673318). （No.61673318）
