供应链协商调度模型与算法

研究了由一个制造商和一个分销商组成的供应链上分销商协商调度问题.此供应链中,制造商比分销商有更强的影响力,先于分销商进行调度.制造商与分销商之间不共享作业处理时间.为了改善分销商调度,建立了基于补偿的分销商协商模型,设计了保留信息私有性的协商调度策略,提出并分析了协商调度下制造商调度算法以及基于生态种群竞争的分销商协同演化调度算法.仿真实验结果表明,分销商协商调度模型与算法能够有效改善分销商调度性能,在不增加制造商调度成本的条件下,可最大程度地削减分销商调度成本超过25％.此外,提出的竞争协同演化算法能够获得比遗传算法、粒子群算法和蚁群算法更好的调度解.

Negotiated Scheduling Model and Algorithms of Supply Chain

The negotiated scheduling problem of distributor is studied for a supply chain that consists of a manufacture and a distributor. The manufacturer is more influential than the distributor. It makes scheduling decisions followed by the distributor. The manufacture and distributor do not share information during the process time of any job. To improve scheduling results of the distributor, a negotiation model is built based on compensation mechanism. A negotiated scheduling strategy with information privacy is designed. A distributor negotiation-scheduling algorithm that consists of a scheduling algorithm of the manufacturer and ecologic population competition based coevolutionary algorithm of the distributor is designed and analyzed. Simulation experiments show that the negotiated scheduling of the distributor can effectively improve the scheduling performance of the distributor. Scheduling cost of the distributor can be cut down over 25% while the scheduling performance of the manufacturer does not become worse. Moreover, the proposed coevolutionary algorithm can obtain better scheduling solutions than the genetic, particle swarm optimization, and ant colony optimization algorithms.