基于多代理协作与作业整合的物流任务分配问题研究

Study on Logistics Task Allocation Based on Multi-agent Collaboration and Job Integration

为提高物流服务集成商对物流资源协同运作的效果,对存在多代理人协作和作业整合情况下的物流任务分配问题进行了研究。综合考虑了各代理人在物流活动协作过程中所产生的衔接成本和衔接时间,结合活动集成和批量整合两种整合策略建立了物流任务分配决策优化模型,并针对该模型提出了遗传和禁忌搜索混合优化算法求解。数值实验验证了混合算法是可行的,禁忌搜索提高了算法的局部搜索能力。

In this paper, we considered comprehensively the connection cost and time of the various agents in the collaboration of logistics activities, established the logistics task allocation decision optimization model and accordingly proposed the genetic algorithm and tabu search algorithm to solve it.