Budget optimization for a multi-distribution multi-state logistics network with reliability consideration

IF 2.3 2区 工程技术 Q3 ENGINEERING, INDUSTRIAL Quality Technology and Quantitative Management Pub Date : 2022-10-31 DOI:10.1080/16843703.2022.2128241
Yi-Feng Niu, Yichang Song, Xiu-Zhen Xu
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引用次数: 1

Abstract

ABSTRACT This paper models a logistics network as a multi-distribution multi-state flow network (MFN) in which each arc has a random capacity characterized by more than one probability distribution under different budget allocations. An optimization model is constructed to minimize the total budget required for the network to achieve a given reliability level. By integrating a novel budget vector method with the well-known binary search method, an effective and efficient algorithm is developed to solve the optimization model, together with analyses on the computational complexity. A practical implementation on a simple network is presented to illustrate the proposed method, and the computational efficiency is explored via numerical examples. Finally, a real case study is provided to showcase the application of the proposed model and method.
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考虑可靠性的多配送多状态物流网络预算优化
摘要本文将物流网络建模为一个多分布多状态流网络(MFN),其中在不同的预算分配下,每个弧线具有一个以上概率分布特征的随机容量。建立了一个优化模型,以使网络达到给定的可靠性水平所需的总预算最小。将一种新的预算向量法与著名的二分搜索法相结合,提出了一种有效的求解优化模型的算法,并对计算复杂度进行了分析。给出了在简单网络上的实际实现,并通过数值算例验证了该方法的计算效率。最后,以一个实际案例来说明所提出的模型和方法的应用。
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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来源期刊
Quality Technology and Quantitative Management
Quality Technology and Quantitative Management ENGINEERING, INDUSTRIAL-OPERATIONS RESEARCH & MANAGEMENT SCIENCE
CiteScore
5.10
自引率
21.40%
发文量
47
审稿时长
>12 weeks
期刊介绍: Quality Technology and Quantitative Management is an international refereed journal publishing original work in quality, reliability, queuing service systems, applied statistics (including methodology, data analysis, simulation), and their applications in business and industrial management. The journal publishes both theoretical and applied research articles using statistical methods or presenting new results, which solve or have the potential to solve real-world management problems.
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