Issue |
RAIRO-Oper. Res.
Volume 57, Number 2, March-April 2023
|
|
---|---|---|
Page(s) | 761 - 789 | |
DOI | https://doi.org/10.1051/ro/2022204 | |
Published online | 28 April 2023 |
A bi-objective robust possibilistic cooperative gradual maximal covering model for relief supply chain with uncertainty
1
Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran
2
Department of Industrial and Management Engineering, Pohang University of Science and Technology, 77, Cheongam-ro, Nam-gu, Pohang-si, Gyeongsangbuk-do 37673, South Korea
3
Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Sinchon-dong, Seodaemun-gu, Seoul 03722, South Korea
4
Center for Transdisciplinary Research (CFTR), Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, 162, Poonamallee High Road, Velappanchavadi, Chennai 600077, Tamil Nadu, India
* Corresponding author: bsbiswajitsarkar@gmail.com
Received:
6
May
2022
Accepted:
17
November
2022
The occurrence of natural and artificial disasters due to their unexpected nature requires precise planning and management in the relief supply chain. A major measure in times of crisis is to assist the damaged points. Due to the limitations in the relief process at the time of the accident, relief centers should be opened in appropriate locations that cover the needs of the damaged points in the shortest possible time. Initially, a nonlinear two-level cooperative gradual maximal covering model in relief supply chain is proposed first. The chain includes supply centers, relief, and damaged points under uncertainty of some key parameters. The major goal is to locate the relief centers and determine the allocations and transfer of goods between the two levels. The bi-objective model minimizes the high logistical costs and maximizes damaged points’ coverages with uncertain costs. Different robust possibilistic programming approaches have utilized the given approaches’ performances, and some suitable recommendations are given. The robust possibilistic model provides the best results among all models. The results show that the robust possibilistic programming model outperforms the possibilistic programming model.
Mathematics Subject Classification: 90B06 / 90B05
Key words: Relief supply chain / cooperative gradual maximal covering / network design model / robust possibilistic programming / uncertainty
© The authors. Published by EDP Sciences, ROADEF, SMAI 2023
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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