摘要
针对随机需求下供应链的供销订购冲突问题,提出一种基于Stackelberg主从对策的供应链多轮次协调订货机制,供应商作为主方制定批发价,零售商作为从方以最优订货量和零售价响应,供应商和零售商进行多轮次自主协调。利用粒子群优化算法和遗传算法对该模型进行仿真计算,仿真结果表明:批发价让步策略可以提高整个供应链的利润,验证了粒子群算法在最优解、求解速率和稳定性方面比遗传算法均要更优。
For the problem between production and sales order conflicts in the supply chain under random demand,we put forward a mechanism of multi-round coordinating ordering based on stackelberg game,the supplier is the leader who sets the wholesale price,retailers respond as followers who select optimal order quantity and retail price,the suppliers and retailers coordinate multi-round independently.Particle swarm optimization algorithm and genetic algorithm were used to simulate and calculate the model,through the simulation results,we found that the wholesale price concession strategy can increase the profit of the entire supply chain.By comparing the two solution methods,we verified that the particle swarm algorithm can obtain a better solution more quickly and more stable than genetic algorithm.
作者
孔令豪
瞿勇
冯杭
KONG Ling-hao;QU Yong;FENG Hang(Foundation Department of the University of Naval Engineering,Wuhan 430033,China)
出处
《火力与指挥控制》
CSCD
北大核心
2019年第12期148-152,共5页
Fire Control & Command Control
关键词
随机需求
协调订货
主从对策
粒子群算法
遗传算法
random demand
coordinating orders
stackelberg game
particle swarm optimization-algorithm
genetic algorithm
