Joint optimization for coordinated configuration of product families and supply chains by a leader-follower Stackelberg game
Joint optimization for coordinated configuration of product families and supply chains by a leader-follower Stackelberg game
复制标题
通过领导者-跟随者 Stackelberg 博弈对产品系列和供应链的协调配置进行联合优化
DOI：
10.1016/j.ejor.2015.04.022
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发表时间：
2015-10
影响因子：
6.4
通讯作者：
Anna Valente
中科院分区：
文献类型：
--
作者：
Dong Yang;Jianxin Jiao;Yangjian Ji;Gang Du;Petri Helo;Anna Valente
基于模块配置的产品族设计有利于在保持批量生产效率的同时适应产品多样性。随着制造商在分布式供应链网络中向按订单装配生产的转变，产品族的有效实现需要产品族配置和下游供应链配置的联合决策。现有的产品族和供应链配置联合优化决策模型都是基于“一体化”的方法，即通过将两种不同类型的目标聚合到一个目标函数中，将PFC和SCC决策集成到一个优化问题中。这种假设忽略了复杂的权衡两个不同的决策问题，并未能揭示PFC和SCC的内在耦合。本文制定了一个产品族及其供应链的联合配置的领导者-追随者Stackelberg游戏，制定通过两个层次的分层优化机制，模型PFC和SCC的两个自利的决策者之间的协调。PFC决策被建模为一个上层优化问题（称为领导者）的模块，模块实例和产品变体的最佳选择。SCC决策被建模为一个较低级别的优化问题（称为追随者），响应于上层的决策，以确定最佳的供应链配置和库存策略。建立了主从对策双层联合决策的非线性混合整数规划模型。为求解非线性优化模型，提出并实现了一种带约束推理的双层嵌套遗传算法。以电力Transformer产品族和供应链配置为例，验证了该方法的可行性和潜力。
Product family design by module configuration is conducive to accommodating product variety while maintaining mass production efficiency. Effective fulfillment of product families necessitates joint decision making of product family configuration (PFC) and downstream supply chain configuration (SCC), due to nowadays manufacturers’ moving towards assembly-to-order production throughout a distributed supply chain network. Existing decision models for joint optimization of product family and supply chain configuration are originated from an “all-in-one” approach that assumes both PFC and SCC decisions can be integrated into one optimization problem by aggregating two different types of objectives into a single objective function. Such an assumption neglects the complex tradeoffs underlying two different decision making problems and fails to reveal the inherent coupling of PFC and SCC.This paper formulates joint configuration of a product family and its supply chain as a leader-follower Stackelberg game that is enacted through a bi-level hierarchical optimization mechanism to model the coordination between two self-interested decision makers for PFC and SCC. The PFC decisions are modeled as an upper-level optimization problem (called leader) for optimal selection of modules, module instances, and product variants. The SCC decisions are modeled as a lower-level optimization problem (called follower), which responds to decisions of the upper level in order to determine an optimal supply chain configuration and inventory policies. A nonlinear, mixed integer programming model is formulated for the bi-level joint decision in the leader-follower game. To solve the nonlinear optimization model, a bi-level, nested genetic algorithm with constraint reasoning is developed and implemented. A case study of a power transformer product family and supply chain configuration is reported to demonstrate the feasibility and potential of the proposed leader-follower game-theoretic method.
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