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Uncapacitated \(p\)-hub location problem with fixed costs and uncertain flows

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Abstract

Hub location problem is an important problem and has many applications in various areas, such as transportation and telecommunication. Since the problem involves long-term strategic decision, the future flows will change with time. However, it is difficult or costly to obtain the data of flows, which implies that it is necessary to consider hub location problems in the absence of data. A commonly used way is to estimate future flows by experts’ subjective information. As a result, this paper presents a new uncapacitated \(p\)-hub location problem, in which the flows are described by uncertain variables. Two uncertain programming models are formulated to respectively minimize the expected cost and the \(\alpha \)-cost with the corresponding constraints. Equivalent forms are given when the information about uncertainty distributions of flows is further provided. A genetic algorithm is designed to solve the proposed models and its effectiveness is illustrated by numerical examples.

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Acknowledgments

This work was supported in part by National Natural Science Foundation of China (Nos. 71371019 and 71332003), in part by the Program for New Century Excellent Talents in University (No. NCET-12-0026) and in part by State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University (No. RCS2014ZQ001).

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Authors and Affiliations

  1. School of Economics and Management, Beihang University, Beijing, 100191, China

    Zhongfeng Qin

  2. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, 100044, China

    Yuan Gao

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  1. Zhongfeng Qin
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  2. Yuan Gao
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Correspondence to Yuan Gao.

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Qin, Z., Gao, Y. Uncapacitated \(p\)-hub location problem with fixed costs and uncertain flows. J Intell Manuf 28, 705–716 (2017). https://doi.org/10.1007/s10845-014-0990-8

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  • DOI: https://doi.org/10.1007/s10845-014-0990-8

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