Mathematical formulations for multi-period network design with modular capacity adjustments

IF 1.1 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Infor Pub Date : 2023-07-26 DOI:10.1080/03155986.2023.2229208
Warley Almeida Silva, S. D. Jena, Karan Jeswani
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引用次数: 0

Abstract

Abstract Network design problems are at the heart of several applications in domains such as transportation, telecommunication, energy and natural resources. This paper proposes a new multi-period network design problem variant, in which modular capacities can be added or reduced along the planning horizon in order to adapt to demand changes. The problem further allows to represent economies of scales in function of the total arc capacity, a detail that has typically been overlooked in the literature. This paper particularly emphasizes the different alternatives to formulate the problem. We propose two different mixed-integer programming formulations and analyze further modeling alternatives. We theoretically compare the strength of all formulations and evaluate their computational performance in extensive experiments. The results suggest that a recent modeling technique using more precise decision variables yields the strongest formulation, which also results in significantly faster solution times. The use of this formulation may therefore be beneficial when considering similar problem variants. Finally, we also evaluate the economical benefits of the features introduced in this new problem variant, indicating that both the selection of the capacity levels and the capacity adjustment along time are likely to result in significant cost savings.
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具有模块化容量调整的多周期网络设计的数学公式
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来源期刊
Infor
Infor 管理科学-计算机:信息系统
CiteScore
2.60
自引率
7.70%
发文量
16
审稿时长
>12 weeks
期刊介绍: INFOR: Information Systems and Operational Research is published and sponsored by the Canadian Operational Research Society. It provides its readers with papers on a powerful combination of subjects: Information Systems and Operational Research. The importance of combining IS and OR in one journal is that both aim to expand quantitative scientific approaches to management. With this integration, the theory, methodology, and practice of OR and IS are thoroughly examined. INFOR is available in print and online.
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