随着物流行业的快速发展,货物运输需求和仓储需求也在不断增加.在构建物流网络的同时,需考虑车辆路径的配送中心选址问题,而现实中这两个问题是互相影响的.因此,本文建立了以免疫算法为框架,以蚁群算法为核心的综合算法模型.模型第一阶段改进了蚁群算法的禁忌搜索,并融合免疫算法;第二阶段设计了免疫-蚁群算法来求解车辆路径和配送中心选址的相互影响关系,并结合算例数据给出全局最优成本.算例结果表明,该综合算法模型明显优于传统免疫选址-蚁群寻优算法,可节约49.5%的总成本,验证了算法的可行性和有效性.%With the rapid development of logistics industry, the demand for freight transportation and warehousing is also increasing. During the design phase of a logistics network, the vehicle routing problem and distribution center location problems are inter-related and need to be considered at the same time. This paper develops an integrated meta-heuristic-based framework to simultaneously solve these two problems. In the first stage, the taboo search of ant colony algorithm is improved and the immune algorithm is integrated; at the second stage, the immune-ant colony algorithm is designed to capture the inter-relationship between the vehicle routing problem and distribution center location problem. A numerical example is then provided to verify the proposed method. The results show that compared with the traditional immune location-ant colony optimization algorithm, the overall method can save 49.5% of the total cost.
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