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Optimizing Cooperative Advertizing, Profit Sharing, and Inventory Policies in a VMI Supply Chain: A Nash Bargaining Model and Hybrid Algorithm

机译:在VMI供应链中优化合作广告,利润共享和库存策略:纳什讨价还价模型和混合算法

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摘要

Members in a vendor managed inventory (VMI) supply chain make joint decisions on inventory policy and cooperative advertizing by capitalizing on their interactions. However, very few investigations have been reported to develop methods to facilitate such joint decision making due to the modeling difficulty and computation complexity. This study is, thus, to address the joint VMI, cooperative advertizing, and profit-sharing decision making in a coordinative way. It considers a two-level VMI supply chain including a manufacturer and retailers, and deals with many decisions, e.g., chain members’ advertizing investments profit sharing. A nonlinear mixed integer Nash bargaining model is developed to model the complex joint decision making of ( +1) players. In view of the difficulties in model solving, this study further develops a solution methodology, including an integrated model and hybrid algorithm for obtaining optimal solutions. Thanks to the integrated model, the hybrid algorithm, which is developed based on analytical methods, a genetic algorithm, and a Lagrange multiplier method, obtains optimal solutions to the Nash bargaining model while greatly reducing computation complexity. Numerical examples demonstrate the validity of the Nash bargaining model and the effectiveness of the solution methodology. Finally, a number of managerial implications are drawn based on sensitivity analysis.
机译:供应商管理的库存(VMI)供应链中的成员通过利用其交互作用来制定库存策略和合作广告的联合决策。然而,由于建模困难和计算复杂性,很少有研究报道开发有助于这种联合决策的方法。因此,本研究旨在以协调的方式解决联合VMI,合作广告和利润分享决策的问题。它考虑了包括制造商和零售商在内的两级VMI供应链,并处理了许多决策,例如,链成员宣传广告投资收益分成。非线性混合整数纳什讨价还价模型被开发来建模(+1)参与者的复杂联合决策。鉴于模型求解中的困难,本研究进一步开发了一种求解方法,包括用于获得最优解的集成模型和混合算法。多亏了集成模型,基于分析方法,遗传算法和拉格朗日乘数法开发的混合算法获得了纳什议价模型的最优解,同时大大降低了计算复杂度。数值算例说明了纳什讨价还价模型的有效性以及求解方法的有效性。最后,基于敏感性分析得出了许多管理意义。

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