Title: Solving a stochastic multi-objective and multi-period hub location problem considering economic aspects by meta-heuristics: application in public transportation

Authors: Mahdi Hamid; Mahdi Bastan; Mojtaba Hamid; Farrokh Sheikhahmadi

Addresses: School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran ' School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran; Department of Industrial Engineering, University of Eyvanekey, Garmsar, Iran ' Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran ' Department of Business Information Technology, Pamplin College of Business Virginia Tech, 1030 Pamplin Hall, Blacksburg, VA 24061, USA

Abstract: In this paper, a multi-objective scenario based mathematical model is presented for the capacitated hub location problem in public transportation considering economic and investment aspects. Three objective functions are regarded in the presented mathematical model. The first one aims to minimise the total costs considering the possibility of investing the unused budget at each period. The second one aims to minimise the total processing time in the hub network at each period. The last one aims to minimise the maximum distance between each pair of origin-destination nodes in the network. To solve the model, three multi-objective meta-heuristic algorithms are developed, namely S metric selection evolutionary multi-objective optimisation algorithm (SMS-EMOA), multi-objective imperialist competitive algorithm (MOICA) and non-dominated sorting genetic algorithm (NSGA-II). Finally, developed algorithms are compared to each other based on several comparison measures using a relatively novel statistical approach.

Keywords: hub location problem; multi-period hub location problem; uncertainty; economic aspects; multi-objective evolutionary algorithms.

DOI: 10.1504/IJCAT.2019.100304

International Journal of Computer Applications in Technology, 2019 Vol.60 No.3, pp.183 - 202

Received: 29 Oct 2018
Accepted: 21 Nov 2018
Published online: 25 Jun 2019 *

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