灾害响应条件下定位-分配-路由救援的双目标随机模型:加速本德斯分解法

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Complexity Pub Date : 2024-07-02 DOI:10.1155/2024/8838354
Behrooz Baygan, Ahmad Mehrabian, Mahdi Yousefi Nejad Attari, Mohammad Jafar Doostideilami
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引用次数: 0

摘要

问题陈述。在灾后阶段提供适当和及时的救援对于最大限度地减少灾民和人员伤亡非常重要。有必要对受灾点的需求进行评估,并在尽可能短的时间内提供救援,避免浪费时间。为此,必须确定护理中心、临时住宿中心的位置,以及分发重要物品和医疗用品的路线。建议采用的方法。本文采用基于情景的随机规划数学模型,对灾后救援进行了讨论。此外,本文还关注了利用路由分配重要物品的问题。贡献。通过使用ε约束方法,为模型的目标实现了一个强有效解,同时还对模型的一些参数进行了敏感性分析。此外,本文还提出了一种加速随机弯曲分解算法来解决模型问题。为了加快求解算法的收敛速度,本文引入了有效不等式,以获得更高质量的下限。研究结果研究结果表明,同时考虑救灾物资的疏散和分发过程可以改善救灾物流过程。
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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A Bi-Objective Stochastic Model of Locating-Allocating-Routing Relief and Rescue in Disaster Response Conditions: An Accelerated Benders Decomposition

Problem Statement. Proper and timely relief in the postdisaster phase is very important to minimize victims and casualties. It is necessary to assess the needs of the affected points and provide relief in the shortest possible time without wasting time. For this purpose, it is necessary and vital to determine the location of care centers, temporary accommodation centers, and routing to distribution vital and medical items. The Proposed Approach. In this paper, using a scenario-based stochastic planning mathematical model, postdisaster relief is discussed. Also, attention has been paid to the distribution of vital items by using routing. Contributions. By using the epsilon constraint method, a strong efficient solution has been achieved for model’s objectives, and also a sensitivity analysis has been performed on some of the model’s parameters. Also, an accelerated stochastic benders decomposition algorithm is suggested to solve the problem modeled in this paper. To speed up the convergence of the solution algorithm, valid inequalities are introduced to get better quality lower bounds. Results. The results of the research show that the simultaneous consideration of the relief evacuation and distribution process improves the relief logistics process.

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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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