Mathematical modeling for a p-mobile hub location problem in a dynamic environment by a genetic algorithm

Bashiri, M, Rezanezhad, M, Tavakkoli-Moghaddam, R and Hasanzadeh, H 2018, 'Mathematical modeling for a p-mobile hub location problem in a dynamic environment by a genetic algorithm', Applied Mathematical Modelling, vol. 54, pp. 151-169.

Document type: Journal Article
Collection: Journal Articles

Title Mathematical modeling for a p-mobile hub location problem in a dynamic environment by a genetic algorithm
Author(s) Bashiri, M
Rezanezhad, M
Tavakkoli-Moghaddam, R
Hasanzadeh, H
Year 2018
Journal name Applied Mathematical Modelling
Volume number 54
Start page 151
End page 169
Total pages 19
Publisher Elsevier
Abstract In this study, a new mobile p-hub location problem in a dynamic environment is proposed, where there are mobile facilities inside hub nodes that can be transferred to other nodes in the next period. Mobile facilities have a mobility feature and can be transferred to other nodes in order to meet demand. Using such facilities will save extra hub establishment and closing costs in networks. This approach can be used in some real-world applications with rapidly changing demand, such as mobile post offices or emergency medical service centers, because designing immobile hub networks may be less efficient. In addition, designing dynamic hub networks entails establishing and closing costs in different periods. The model also considers a mobility infrastructure of hub facilities. The numerical examples confirm that a mobile hub network is more efficient than an immobile hub network in a dynamic environment. The effect of different parameters on the model is analyzed to consider its applicability conditions. A genetic algorithm, along with tuned parameters and a simulated annealing algorithm, are proposed to solve the model in large instances. Proposing of a model considering mobility feature in the hub location networks, proving its efficiency and finally proposing a proper solution algorithm are main contributions of this study. The model and solutions algorithms were analyzed by more numerical instances using Australia post (AP) dataset.
Subject Applied Mathematics not elsewhere classified
Numerical and Computational Mathematics not elsewhere classified
Keyword(s) Dynamic environment
Genetic algorithm
Greedy local search
Mobile hub location
Mobility infrastructure
DOI - identifier 10.1016/j.apm.2017.09.032
Copyright notice © 2017 Elsevier Inc. All rights reserved.
ISSN 0307-904X
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