首页> 外文期刊>Applied Mathematical Modelling >An integrated multi-product, multi-buyer supply chain under penalty, green, and quality control polices and a vendor managed inventory with consignment stock agreement: The outer approximation with equality relaxation and augmented penalty algorithm
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An integrated multi-product, multi-buyer supply chain under penalty, green, and quality control polices and a vendor managed inventory with consignment stock agreement: The outer approximation with equality relaxation and augmented penalty algorithm

机译:带有惩罚,绿色和质量控制策略的集成多产品,多买方供应链,以及带有寄售库存协议的供应商管理的库存:具有等式松弛和增额罚款算法的外部近似

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It is of great importance to develop an optimal supply chain (SC) batch-sizing policy that collectively embodies green policies and a vendor-managed inventory (VMI) with consignment stock (CS) agreement. This article provides a mathematical model that includes the buyers' total cost (TC) and the vendor's TC in an SC under penalty, green, and quality control (QC) policies and a VMI-CS agreement. The proposed model is a multiproduct, multi-buyer model and has real stochastic constraints. Moreover, the model differentiates between the holding costs for financial and nonfinancial components, in which the first includes the investment in the space and the second includes the cost due to physical storage, movement, and insurance of the products. Financial components are carried by the vendor on implementation of the VMI-CS agreement, while holding costs for stocking items in the buyers' warehouses are carried by the buyers as nonfinancial components. The objective is to determine the optimal batch-sizing policy with the minimum TC in the integrated SC that finds both the number of the vendor's batches for each of the transported products and the volume of the batches transported to the buyers so as to minimize the TC of the integrated SC while the stochastic constraints are satisfied. Because of the complexity of the optimization model and mathematical formulations, an outer approximation with equality relaxation and augmented penalty algorithm is presented to determine the optimal batch-sizing policy. With application of this technique, the large-scale and hard-to-solve mixed-integer nonlinear programming problem is minimized. The optimality criteria results obtained in numerical examples and sensitivity analysis demonstrate the excellent performance of the method used. Finally, managerial insights, analytical results, and future research directions are provided. (C) 2018 Elsevier Inc. All rights reserved.
机译:制定最能体现绿色政策的最佳供应链(SC)批量调整策略和带有寄售库存(CS)协议的卖方管理库存(VMI)至关重要。本文提供了一个数学模型,其中包括在惩罚,绿色和质量控制(QC)策略以及VMI-CS协议的约束下,买方的总成本(TC)和卖方的TC。所提出的模型是多产品,多购买者模型,并且具有实际的随机约束。此外,该模型区分了财务和非财务部分的持有成本,其中第一部分包括空间投资,第二部分包括产品的实物存储,运输和保险费用。财务部分由卖方在执行VMI-CS协议时承担,而买方仓库中的库存商品的存放成本则由买方作为非财务部分承担。目的是在集成式SC中确定具有最小TC的最佳批次大小策略,以找到每种运输产品的供应商批次数量和运输到买方的批次数量,从而最大程度地减少TC满足随机约束条件的同时,对集成SC进行优化。由于优化模型和数学公式的复杂性,提出了使用等式松弛和增罚算法的外部近似方法,以确定最佳的批量策略。通过应用该技术,可以最大程度地解决大规模且难以解决的混合整数非线性规划问题。在数值示例和灵敏度分析中获得的最佳标准结果证明了所用方法的出色性能。最后,提供了管理见解,分析结果以及未来的研究方向。 (C)2018 Elsevier Inc.保留所有权利。

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