Selecting warehouse location by means of the balancing and ranking method with an interval approach

Behnam Malmir, Rahim Moein, S. K. Chaharsooghi
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引用次数: 7

Abstract

Selecting the proper warehouse location has been always one of the most important and strategic challenges in the optimization process of a logistics system. Such decisions have a great importance for companies because they are costly and difficult to reverse, and entail a long term commitment. Many quantitative and qualitative factors affect the selection of the warehouse location as a long term decision. A new balancing and ranking method combined with an interval data approach has been presented in this paper for solving a warehouse location selection problem. This method involves a three-step procedure to derive an overall complete final order of the warehouses which are already selected for the decision making. The procedure involves the definition of an outranking matrix based on the criteria values for all the available warehouse locations while taking into account the frequency of superiority of one location over others. The ordering of the warehouse locations has been performed based on the information of an advantages-disadvantages table, the distance travelled after final balancing, and the provisional order of locations. This is referred to as the triangularisation. It should be noted that unlike other MCDM models, the proposed method does not require weights for the decision making criteria. In addition, the proposed approach is much more flexible than the conventional methods in some other aspects. To demonstrate the procedural implementation of the proposed method and illustrate its effectiveness, it was applied to a case study and the results are evaluated and verified.
采用区间均衡排序法进行仓库选址
在物流系统优化过程中,选择合适的仓库位置一直是最重要的战略挑战之一。这样的决定对公司来说非常重要,因为它们成本高昂,难以逆转,而且需要长期的承诺。作为一项长期决策,许多定量和定性因素影响着仓库选址的选择。本文结合区间数据法,提出了一种新的平衡排序方法来解决仓库选址问题。该方法包括一个三步过程,以导出已经为决策选择的仓库的整体完整最终订单。该程序包括根据所有可用仓库位置的标准值定义一个优先矩阵,同时考虑到一个位置比其他位置优越的频率。仓库位置的排序是根据利弊表的信息、最终平衡后的行进距离和位置的临时顺序来执行的。这被称为三角化。值得注意的是,与其他MCDM模型不同,本文提出的方法不需要对决策标准进行权重要求。此外,所提出的方法在其他一些方面比传统方法更加灵活。为了演示所提出方法的程序实施和说明其有效性,将其应用于一个案例研究,并对结果进行了评估和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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