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

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• 作者：Zhongfeng Qin ; Yuan Gao
• 关键词：\(P\) ; hub location problem ; Uncertain variable ; Uncertain measure ; Expected value model ; Chance ; constrained programming
• 刊名：Journal of Intelligent Manufacturing
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：28
• 期：3
• 页码：705-716
• 全文大小：
• 刊物类别：Business and Economics
• 刊物主题：Production; Manufacturing, Machines, Tools; Control, Robotics, Mechatronics;
• 出版者：Springer US
• ISSN：1572-8145
• 卷排序：28

文摘

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.