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考虑随机需求下多供应商和多零售商的生产-库存-运输联合优化问题.在联合优化时,首先利用最近邻算法将各零售商分成不同区域,分区后问题转化为随机需求下单供应商对多零售商的生产-库存-运输联合优化问题.在每个分区内,由供应商统一决策其分区内各零售商的送货量和送货时间.利用粒子群算法和模拟退火算法相结合的两阶段算法求出最优送货量、最优运输路径和最大期望总利润.然后采用收入共享契约将增加的利润合理分配给各供应商和各零售商,使各方利润都得到增加,从而促使各方愿意合作.通过数值算例验证了联合优化模型优于独立决策模型.
Consider the production-inventory-transport joint optimization problem of multi-suppliers and multi-retailers under stochastic demand.In the joint optimization, firstly, the nearest neighbor algorithm is used to divide each retailer into different regions, and the problem of sub-region is transformed into the single-supplier with random demand For multiple retailers, the production-inventory-transport joint optimization problem, in each sub-region, the supplier unifies the decision of the delivery volume and delivery time of each retailer in the sub-region.Using particle swarm optimization and simulated annealing algorithm The two-stage algorithm to find the optimal delivery volume, the optimal transport path and the maximum expected total profit.And then use the revenue sharing contract to distribute the increased profit rationally to the suppliers and retailers so that the profits of all parties are increased, So that all parties are willing to cooperate.Through numerical examples, it is verified that the joint optimization model is better than the independent decision model.