基于混合多策略免疫算法的配送中心选址研究  

A Study of Distribution Centre Locations Based on Hybrid Multi-strategy Immune Algorithm

作　　者：都威 黄琦 刘妍 DU Wei;HUANG Qi;LIU Yan(School of Electronic Information,Xi'an Polytechnic University,Xi'an 710699,China)

机构地区：[1]西安工程大学电子信息学院,陕西西安710699

出　　处：《物流科技》2024年第23期8-13,共6页Logistics Sci Tech

基　　金：国家自然科学基金项目(51905405)。

摘　　要：为提升基本免疫算法的寻优性能,降低城市物流配送中心选址的成本,提出一种混合多策略免疫算法。首先,使用Tent混沌映射快速构成均匀分布的初始解,丰富种群的多样性;其次,结合差分进化算法中的更新机制增强免疫算法的寻优能力,并使用线性增量规则平衡算法的全局和局部搜索能力;最后,采用非均匀变异策略对整个解空间进行干扰,避免算法的“早熟”现象。实验结果表明,所提出的算法收敛速度更快,鲁棒性更好,并能在短时间内给出物流成本更低的选址方案。In order to improve the optimization performance of the basic Immune Algorithm and reduce the cost of urban logistics distribution centre location,a Hybrid multi-strategy Immunity Algorithm is proposed.Firstly,Tent chaotic mapping is used to quickly form a uniformly distributed initial solution to enrich the diversity of the population.Second,the update mechanism in the differential evolutionary algorithm is combined to enhance the optimization search capability of the Immune Algorithm,and the linear incremental rule is used to balance the global search capability and local search capability of the algorithm.Finally,the non-uniform mutation strategy is used to interfere with the whole solution space to avoid the"premature"phenomenon of the algorithm.The experimental results show that the proposed location algorithm not only has faster convergence speed and better robustness,but also can give a location plan with lower logistics cost in a short time.

关 键 词：选址应用 免疫算法 混沌映射 差分进化 非均匀变异 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] F252.14[自动化与计算机技术—计算机科学与技术]