带选址的关联运输调度问题研究  

Study on incident vehicle routing problem with site selection

作　　者：乐峰[1] 蔡延光[1] 汤雅连[1] 王芳婷[1] 

机构地区：[1]广东工业大学自动化学院,广东广州510006

出　　处：《微型机与应用》2013年第12期63-66,共4页Microcomputer & Its Applications

摘　　要：对零售点的选址问题和关联货物配送问题建模,分别应用改进的混沌遗传算法和免疫克隆选择算法求解该模型,前者采用混沌初始化方法产生初始种群,使种群具有较好的多样性,并采用混沌搜索策略以提高算法的收敛速度和全局搜索能力。最后比较两种算法的求解结果,结果证实了改进的混沌遗传算法求解该模型的有效性与优越性。Building a mathematical model for retail site selection planning problem and incident vehicle routing problem（IVRP）, and adapting improved chaotic genetic algorithm（ICGA） and immune clonal selection algorithm（ICSA） to solve this problem. ICGA uses the chaotic initialization method to generate initial population, thus it has better diversity, and chaotic search strategy can speed up its convergence and enhance its global search ability. Comparing the rusuhs which have solved by the two algorithms, the results show ICGA has effectiveness and advantage to solve this model.

关 键 词：零售点选址 关联运输调度问题 改进混沌遗传算法 免疫克隆选择算法 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]