Journal of Computer Applications ›› 2021, Vol. 41 ›› Issue (7): 2100-2107.DOI: 10.11772/j.issn.1001-9081.2020101617

Special Issue: 前沿与综合应用

• Frontier and comprehensive applications • Previous Articles     Next Articles

Channel structure choice of closed-loop supply chain under uncertain demand and recovery

ZHANG Meng1, GUO Jianquan2   

  1. 1. Business School, U niversity of Shanghai for Science and Technology, Shanghai 200093, China;
    2. Shanghai-Hamburg College, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2020-10-19 Revised:2021-01-14 Online:2021-07-10 Published:2021-01-27
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (71471110, 71631007), the Shanghai Science and Technology Innovation Action Project (DZ1201402), the University Capacity Building Project of Science and Technology Commission of Shanghai Municipality (16040501500).


张盟1, 郭健全2   

  1. 1. 上海理工大学 管理学院, 上海 200093;
    2. 上海理工大学 上海-汉堡国际工程学院, 上海 200093
  • 通讯作者: 张盟
  • 作者简介:张盟(1994-),女,河北石家庄人,硕士研究生,主要研究方向:供应链管理、物流工程;郭健全(1972-),男,河南鲁山人,副教授,博士,主要研究方向:国际贸易、国际商务、国际物流、供应链管理。
  • 基金资助:

Abstract: Aiming at the optimal choice of sales channel structure in the closed-loop supply chain, considering the uncertainty of market demand and quality level of recycled products, four average gross profit models for the closed-loop supply chain system with four sales channel structures under the government differentially weighted subsidy were constructed with the objective of maximizing the gross profit. Firstly, Fuzzy Chance Constrained Programming (FCCP) method was used to transform the fuzzy constraints into clear corresponding expressions equivalently. Then, Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) were used to solve numerical examples of the model comparatively. Finally, sensitivity analysis was performed on the parameters. The results show that the maximum difference ratio of the above two algorithms is 0.018%, indicating that both algorithms do not fall into the local optimal solution, which verifies the validity of the algorithms and the confidence of the models. Enterprises can formulate optimal recycling, production and sales strategies according to different confidence levels of the potential demands, choose the optimal channel structure and increase the gross profit gradually.

Key words: uncertain demand and recovery, channel structure choice, Fuzzy Chance Constrained Programming (FCCP) method, government differentially weighted subsidy, Particle Swarm Optimization (PSO) algorithm, Genetic Algorithm (GA)

摘要: 针对闭环供应链中销售渠道结构的最优选择问题,考虑市场需求和回收品质量水平的不确定性,以总利润最大化为目标,构建了政府差别权重补贴下四种销售渠道结构闭环供应链系统的四个平均总利润模型。首先运用模糊机会约束规划(FCCP)法将模糊约束等价变换为清晰对应式,然后采用粒子群优化(PSO)算法和遗传算法(GA)对模型算例进行对比求解,最后对参数进行了灵敏度分析。结果表明,上述两种算法的差值比率最大为0.018%,表明两种算法均未陷入局部最优解,验证了算法的效度和模型的信度。企业可以根据潜在需求的不同置信水平制定最优回收、生产和销售策略,选择最优的渠道结构并逐渐提高总利润。

关键词: 需求和回收不确定, 渠道结构选择, 模糊机会约束规划法, 政府差别权重补贴, 粒子群优化算法, 遗传算法

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