Abstract: In view of the interference of dynamic events in distribution process, this paper proposes the multi-products joint distribution vehicle routing problem. Based on the dynamic events in uncertain circumstance, this paper proposes a space-time passion distribution method to generate dynamic customers and buils the multi-products joint distribution vehicle routing problem with uncertain circumstance accordingly for the sake of the minimum the overall operating cost and fixed cost. For the particularity of this issues, a combination of genetic algorithm and Tabu search algorithm is designed and its performance is tested by a set of specific examples. The results show that the multi-products joint distribution method is superior to the single one, and the improved combinational algorithm has a better find-best ability.

Key words: logistics engineering, joint distribution, a combination of genetic algorithm and Tabu search algorithm, multi-products, vehicle routing problem, uncertainty

摘要： 针对动态事件对配送过程的干扰问题，提出多品类共同配送车辆路径优化问题。基于对不确定环境下动态客户时空特性的分析，提出利用时空泊松分布生成动态客户的方法；并从整体运营成本及车辆固定成本入手，建立不确定环境下多品类共同配送模型；鉴于考虑模型的特殊性，设计遗传-禁忌搜索组合优化算法，结合具体算例对模型和算法性能进行验证。结果表明，提出的多品类共同配送方法优于单品类配送方法，且改进后的遗传-禁忌搜索算法具有更强的寻优能力。

关键词: 物流工程, 共同配送, 遗传禁忌算法, 多品类, 车辆路径问题, 不确定性