Version 1
: Received: 26 October 2024 / Approved: 27 October 2024 / Online: 28 October 2024 (12:24:54 CET)
How to cite:
Babaei, S.; Khalaj, M.; Keramatpour, M.; Enayati, R. Optimizing Green Supply Chain: A Hub Location Model Utilizing NSGAII and MOPSO Algorithms for Enhanced BTS Site Coverage in Telecommunication Networks. Preprints2024, 2024102111. https://doi.org/10.20944/preprints202410.2111.v1
Babaei, S.; Khalaj, M.; Keramatpour, M.; Enayati, R. Optimizing Green Supply Chain: A Hub Location Model Utilizing NSGAII and MOPSO Algorithms for Enhanced BTS Site Coverage in Telecommunication Networks. Preprints 2024, 2024102111. https://doi.org/10.20944/preprints202410.2111.v1
Babaei, S.; Khalaj, M.; Keramatpour, M.; Enayati, R. Optimizing Green Supply Chain: A Hub Location Model Utilizing NSGAII and MOPSO Algorithms for Enhanced BTS Site Coverage in Telecommunication Networks. Preprints2024, 2024102111. https://doi.org/10.20944/preprints202410.2111.v1
APA Style
Babaei, S., Khalaj, M., Keramatpour, M., & Enayati, R. (2024). Optimizing Green Supply Chain: A Hub Location Model Utilizing NSGAII and MOPSO Algorithms for Enhanced BTS Site Coverage in Telecommunication Networks. Preprints. https://doi.org/10.20944/preprints202410.2111.v1
Chicago/Turabian Style
Babaei, S., Mehdi Keramatpour and Ramin Enayati. 2024 "Optimizing Green Supply Chain: A Hub Location Model Utilizing NSGAII and MOPSO Algorithms for Enhanced BTS Site Coverage in Telecommunication Networks" Preprints. https://doi.org/10.20944/preprints202410.2111.v1
Abstract
Today, the facility location planning issue mainly belongs to the long-term operational and strategic level of large public and private organizations, and the significant costs associated with facility location, construction, and operation have turned location research into long-term decision-making. Presenting a hub location model for the green supply chain can address the current status of facilities and significantly improve demand coverage at an acceptable cost. Therefore, in this study, a network of facilities for hub location in the service site domain, considering existing and potential facilities under probable scenarios, has been proposed. After presenting the mathematical model, validation was performed on a small scale, followed by sensitivity analysis of the main parameters of the model. Furthermore, a metaheuristic algorithm was employed to analyze the NP-Hardness of the model. Additionally, to demonstrate the efficiency of the model, two metaheuristic algorithms, NSGAII and MOPSO, were developed. Based on the conducted analysis, it can be observed that the computational time increases exponentially with the size of sample problems, indicating the NP-Hardness of the problem. However, the NSGAII algorithm performs better in terms of computational time for medium-sized problems compared to the MOPSO algorithm.
Keywords
Facility Location; maximum coverage; telecommunication; Hub Location; NSGAII; MOPSO
Subject
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
