Abstract: To overcome the deficiencies of a multi-center joint distribution network optimization study based on the vehicle sharing and collaborative alliance construction,an alliance optimization strategy of the multi-center joint distribution network based on vehicle sharing was proposed.A bi-objective optimization model including the minimization of multi-period logistics operating costs and number of vehicles was established.An improved K-means clustering algorithm was devised to consider the spatial geographic locations of customers and service time windows,and then a CW-NSGA-Ⅱ hybrid algorithm was proposed.This hybrid algorithm designed a selective exchange mechanism,which enhanced the algorithm's global and local optimization capability.Through the comparison and analysis with Multi-Objective Genetic Algorithm (MOGA) and Multi-Objective Particle Swarm Optimization (MOPSO) algorithm,the validity of the model and the algorithm was verified.An improved Shapley value method was presented to study the profit allocation optimization scheme of multi-center joint distribution,then the collaborative alliance sequence selection among multiple centers was studied,and the stability of the collaborative alliance scheme was verified by comparison with different profit allocation methods.The proposed method was verified via a case study,and the multi-center collaborative alliance sequences under different vehicle sharing modes were analyzed and discussed.The results showed that the proposed method could achieve the reasonable configuration of distribution resources and improve the stability of the collaborative alliances,which provided reference and method support for logistics distribution network optimization based on resource sharing.

Key words: multi-center joint distribution, vehicle sharing mode, Clarke-Weight fast elitist non-dominated sorting genetic algorithm, profit allocation, alliance stability

摘要： 针对多中心共同配送网络优化研究在车辆共享和合作联盟构建方面存在的不足,提出基于车辆共享的多中心共同配送联盟优化策略。首先,建立了多周期物流运营成本最小化和车辆使用数最小化的双目标优化模型。其次,设计了考虑客户空间地理位置和服务时间窗的K-means时空聚类算法,进而提出一种Clarke-Wright-带精英策略的快速非支配排序遗传算法混合算法,该混合算法设计了算法间的选择性赋予机制,增强了算法的全局和局部寻优能力,并与多目标遗传算法和多目标粒子群算法进行比较分析,进一步验证了模型和算法的有效性。然后,应用改进Shapley值法进行了多中心共同配送的收益分配优化方案研究,进而研究了多中心间的合作联盟序列选择,并比较验证了不同收益分配方法计算的合作联盟方案稳定性。最后,通过实例对所提方法进行了验证,分析探讨了不同车辆共享模式下的多中心合作联盟序列,结果表明该方法能够实现配送资源的合理化配置并提高合作联盟稳定性,可为基于资源共享的物流配送网络优化提供参考和方法支持。

关键词: 多中心共同配送, 车辆共享模式, Clarke-Wright-带精英策略的快速非支配排序遗传算法, 收益分配, 联盟稳定性