Application of Hybrid GA-SA Heuristic for Green Location Routing Problem with Simultaneous Pickup and Delivery
Advances
Volume 1, Issue 1, December 2020, Pages: 1-10
Received: Aug. 18, 2020; Accepted: Sep. 1, 2020; Published: Sep. 10, 2020
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Authors
Setareh Abedinzadeh, Department of Industrial Engineering, University of Science and Culture, Tehran, Iran
Ali Ghoroghi, Department of Computer Engineering, University of Cardiff, Cardiff, Wales
Hamid Reza Erfanian, Department of Mathematics, University of Science and Culture, Tehran, Iran
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Abstract
Satisfaction of customer, either in product quality point of view, or in delivery lead time point of view, is considered as a pivotal challenge among producers and distributers in supply chain. This leads to both augmentation of service level and declining the total costs of the supply chain. In this paper, we regarded a variant of the Location-Routing Problem (LRP) with consideration of green aspects, namely the green LRP with simultaneous pickup and delivery (GLRPSPD). This problem seeks to minimize total cost by simultaneously locating the distribution centers and designing the vehicle routes that satisfy pickup and delivery demand of each customer at the same time, in a way that ecological aspects are observed. The formulated problem was a mixed integer programming (MIP) model and it used, GAMS optimization software for solving that. Finally, to solve the real-size problem in an acceptable time, we considered a hybrid heuristic Genetic Algorithm-Simulated Annealing (GA-SA). The compared solutions of GAMS and those obtained from the hybrid GA-SA depicts that the hybrid heuristic GA-SA is proficient in terms of both computational time and the quality of the solutions obtained.
Keywords
Location-routing Problem, Green Routing, Simultaneous Pickup and Delivery, Hybrid Heuristic Genetic Algorithm-Simulated Annealing
To cite this article
Setareh Abedinzadeh, Ali Ghoroghi, Hamid Reza Erfanian, Application of Hybrid GA-SA Heuristic for Green Location Routing Problem with Simultaneous Pickup and Delivery, Advances. Vol. 1, No. 1, 2020, pp. 1-10. doi: 10.11648/j.advances.20200101.11
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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