随机需求下零售商主导的利润共享模型  

Profit Sharing Model of Retailer's Leading Under Random Demand

作　　者：孔令豪 瞿勇 冯杭 关琦譞 KONG Linghao;QU Yong;FENG Hang;GUAN Qixuan(Joint Service College of National University,Beijing 100080;Department of Foundation,Naval University of Engineering,Wuhan 430033)

机构地区：[1]国防大学联合勤务学院,北京100080 [2]海军工程大学基础部,武汉430033

出　　处：《舰船电子工程》2024年第12期95-100,共6页Ship Electronic Engineering

基　　金：国家社会科学基金军事学项目“军队预算绩效评价指标体系和模型构建研究”(编号:2022-SKJJ-B-095)资助。

摘　　要：市场环境波诡云谲,瞬息万变。论文着眼市场随机需求的情况,围绕供应链的准时化采购问题,提出基于Stackelberg主从对策的供应链利润共享机制。在机制运行过程中,零售商以主方的身份制定并提出价格折扣,供应商以从方的身份提出共同补货期响应。建立利润共享模型,以供应链系统利润最大化为目标,运用粒子群优化和遗传算法仿真计算该模型,仿真结果显示:在利润共享机制下,价格折扣和共同补货期策略可以提高整个供应链的利润;在最优解、求解速率和稳定性方面,粒子群优化都要比遗传算法更优。The market environment is uncertain and rapidly changing.Focusing on the situation of market random demand,this paper puts forward a mechanism of profit-sharing based on Stackelberg game for the problem of JIT purchasing in the supply chain.In the operation of the mechanism,the retailer puts forward the price discount as the main party,suppliers respond who se⁃lect optimal co-replenishment period as the slave party.A profit sharing model is established to maximize the profit of the supply chain system,and the model is simulated by particle swarm optimization algorithm and genetic algorithm.The simulation results show that:under the profit-sharing mechanism,the price discount and co-replenishment period strategies can increase the profit of the entire supply chain.In terms of optimal solution,solving rate and stability,the particle swarm algorithm is superior than genetic algorithm.

关 键 词：随机需求 JIT采购 价格折扣 共同补货期 主从对策 粒子群算法 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]