研究了在制造商占优并优先调度的分销供应链中,多个分销商同时与制造商进行协商以改善自身调度的问题,建立了基于补偿的多目标协商调度模型,提出了同时实施分销商局部演化计算与制造商全局演化计算的新型多目标合作协同演化算法GLCCEC.提出了制造商全局精英解的跳跃渐变解组合策略及全局非支配解集实时更新策略,设计了保持局部作业顺序约束下的分销商局部解全局化动态规划算法.实验结果表明,GLCCEC算法能够在不损害制造商调度的条件下有效改善每个分销商的调度,所获得的非支配解集不仅目标值优于现有的3 种主要合作协同演化算法MOCCGA,NSCCGA,GBCCGA,而且具有良好的解分散度.

It is investigated that multiple distributors simultaneously negotiate with a manufacturer to improve themselves schedules on a distribution supply chain in which manufacturer has stronger power than distributors and does scheduling decision prior to distributors. A compensation based negotiation scheduling model is built. A novel multi-objective cooperative co-evolutionary algorithm (GLCCEC) that concurrently implements local evolutionary computing of distributors and global evolutionary computing of manufacturer is proposed. Global elite solution combination strategy with gradually gene skipping change and real time updating of global non-dominated solution set are designed for manufacturer. A dynamic programming algorithm with constraint of retaining sequence of local schedule is designed in order to get global solution from a local solution of distributor. Computational experiments show that GLCCEC algorithm can effectively improve schedule of each distributor with no deterioration of manufacturer’s schedule. Moreover, the non-dominated solutions of GLCCEC not only are better than that of other best cooperative co-evolutionary algorithms: MOCCGA, NSCCGA, GBCCGA, but also has good spread in solution space.

国家自然科学基金(60904072); 国家教育部博士点新教师基金(20090185120002); 国家教育部人文社科青年基金(09YJC630018); 电子科技大学中央高校基本科研业务经费(103.1.2 E022050205)