Volume 55, Number 3, May-June 2021
|Page(s)||1371 - 1399|
|Published online||08 June 2021|
Capacitated location routing problem with simultaneous pickup and delivery under the risk of disruption
Department of Industrial & System Engineering, Isfahan University of Technology, Isfahan, Iran.
2 IMT Atlantique, Lab-STICC, UBL, F-29238 Brest, France
3 Centre of Excellence in Supply Chain and Transportation (CESIT), KEDGE Business School, Bordeaux, France
* Corresponding author: firstname.lastname@example.org
Accepted: 30 March 2021
This paper develops a new mathematical model to study a location-routing problem with simultaneous pickup and delivery under the risk of disruption. A remarkable number of previous studies have assumed that network components (e.g., routes, production factories, depots, etc.) are always available and can permanently serve the customers. This assumption is no longer valid when the network faces disruptions such as flood, earthquake, tsunami, terrorist attacks and workers strike. In case of any disruption in the network, tremendous cost is imposed on the stockholders. Incorporating disruption in the design phase of the network will alleviate the impact of these disasters and let the network resist disruption. In this study, a mixed integer programming (MIP) model is proposed that formulates a reliable capacitated location-routing problem with simultaneous pickup and delivery (RCLRP-SPD) services in supply chain distribution network. The objective function attempts to minimize the sum of location cost of depots, routing cost of vehicles and cost of unfulfilled demand of customers. Since the model is NP-Hard, three meta-heuristics are tailored for large-sized instances and the results show the outperformance of hybrid algorithms comparing to classic genetic algorithm. Finally, the obtained results are discussed and the paper is concluded.
Mathematics Subject Classification: 90C59
Key words: Reliable capacitated location-routing problem / simultaneous pickup and delivery / disruptions / hybrid algorithms
© The authors. Published by EDP Sciences, ROADEF, SMAI 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://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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