A self-adaptive evolutionary algorithm for a fuzzy multi-objective hub location problem: An integration of responsiveness and social responsibility

In this paper, we present a new multi-objective model for a hub location problem under uncertainty. This model simultaneously considers economic, responsiveness and social aspects in designing a hub-and-spoke network. An M/M/c queuing system is used to calculate waiting time at each hub node and max...

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Bibliographic Details
Published in:Engineering applications of artificial intelligence Vol. 62; pp. 1 - 16
Main Authors: Zhalechian, Mohammad, Tavakkoli-Moghaddam, Reza, Rahimi, Yaser
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.06.2017
Subjects:
Evolutionary algorithm
Hub location problem
Responsiveness
Social responsibility
Uncertainty
Responsiveness
Uncertainty
Hub location problem
Social responsibility
Evolutionary algorithm
ISSN:0952-1976, 1873-6769
Online Access:Get full text
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Summary:In this paper, we present a new multi-objective model for a hub location problem under uncertainty. This model simultaneously considers economic, responsiveness and social aspects in designing a hub-and-spoke network. An M/M/c queuing system is used to calculate waiting time at each hub node and maximize responsiveness. Employment and regional development are selected as social responsibility measures in the proposed model. Furthermore, a hybrid two-phase solution method is proposed based on possibilistic programming, fuzzy multi-objective programming and an efficient algorithm, called self-adaptive differential evolution algorithm. Finally, several numerical experiments and sensitivity analyses are carried out to assess the proposed model and the solution method.
ISSN:0952-1976
1873-6769
DOI:10.1016/j.engappai.2017.03.006