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Vendor-managed inventory in the joint replenishment problem of a multi-product single-supplier multiple-retailer supply chain A teacher-learner-based optimization algorithm

机译:多产品单供应商多零售商供应链联合补货问题中的供应商管理库存基于教师-学习者的优化算法

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Purpose - In this paper, the joint replenishment problem is modeled for a two-level supply chain consisting of a single supplier and multiple retailers that use the vendor-managed inventory (VMI) policy for several products. This paper aims to find the optimal number of products to order in both policies, the optimal times at which each retailer orders the products in the traditional policy and the optimal times at which the supplier orders the product in the VMI policy. Design/methodology/approach - The problem is first formulated into the framework of a constrained integer nonlinear programming model; then, the problem is solved using a teacher-learner based optimization algorithm. As there are no benchmarks available in the literature, a genetic algorithm is used as well to validate the results obtained. Findings - The solutions obtained using both the algorithms for several numerical examples are compared to the ones of a random search procedure for further validation. A real case is solved at the end to demonstrate the applicability of the proposed methodology and to compare both the policies. Research limitations/implications - The paper does not have any special limitations. Practical implications - The study has significant practical implications for the sellers and for the suppliers who have to get the most profit. Also, satisfying the constraints make decision more complicated. Originality/value - This paper has two main originalities. The authors have developed the model of the joint replenishment problem and have contributed in the problem-solving process. They have used a new meta-heuristic and then compared it to a classic one.
机译:目的-在本文中,联合补货问题是针对由单个供应商和多个零售商组成的两级供应链建模的,这些零售商对几种产品使用供应商管理的库存(VMI)策略。本文旨在找到两种策略中要订购的最佳产品数量,传统策略中每个零售商订购产品的最佳时间以及VMI策略中供应商订购产品的最佳时间。设计/方法/方法-首先将问题表述为约束整数非线性规划模型的框架;然后,使用基于教师-学习者的优化算法解决该问题。由于文献中没有基准可用,因此也使用遗传算法来验证获得的结果。结果-将使用两种算法的几个数值示例获得的解决方案与随机搜索过程的解决方案进行比较,以进行进一步的验证。最后解决了一个实际案例,以证明所提出方法的适用性并比较这两种政策。研究局限性/含义-本文没有任何特殊限制。实际意义-该研究对必须获取最大利润的卖方和供应商具有重大的实际意义。同样,满足约束条件会使决策更加复杂。创意/价值-本文有两个主要创意。作者开发了联合补给问题的模型,并为解决问题做出了贡献。他们使用了一种新的元启发式方法,然后将其与经典方法进行了比较。

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