Authors : Ryan Hong; Dylan Hong

Volume/Issue : Volume 10 - 2025, Issue 4 - April

Google Scholar : https://tinyurl.com/4pkmcssy

Scribd : https://tinyurl.com/4njnc824

DOI : https://doi.org/10.38124/ijisrt/25apr1291

Google Scholar

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Note : Google Scholar may take 15 to 20 days to display the article.

Abstract : The 21st century has seen a growing divide between urban and rural areas driven by urban development and migration from rural regions to cities. This shift, along with rising demand, has resulted in complex and unsustainable supply chains that significantly contribute to climate change. In response, many companies are prioritizing the development of more sustainable supply chains to meet customer demand. This paper aims to optimize supply chain logistics by selecting the best meeting points, locations, and vehicle capacities for various query points while fulfilling basic needs to deliver products to retailers at minimal cost. The study will utilize Collective Travel Planning alongside the Maximal Covering Location Problem (MCLP) to create a function capable of computing the most efficient route. This approach differs from previous methods by incorporating both product categories and vehicle capacities, factors that better reflect real-world conditions, including the dynamic fluctuations in supply and demand from both retailers and customers. The proposed function will be evaluated through experiments using synthetic data designed to model realistic-scale problems. The results of these evaluations will help assess the practical applicability and effectiveness of the developed function in optimizing supply chain routes, offering a more sustainable solution for supply chain management in the face of modern challenges.

Keywords : Collective Travel Planning, Maximal Coverage Location Problem, Query Point, Meeting Point.

References :

1. United Nations. (n.d.). Natural disasters occurring three times more often than 50 years ago: New FAO Report | UN News. United Nations. Retrieved from https://news.un.org/en/story/2021/03/1087702
2. United Nations. (2022, May 9). Climate: World getting 'measurably closer' to 1.5-degree threshold | UN News. United Nations. Retrieved from https://news.un.org/en/story/2022/05/1117842#:~:text =There%20is%20a%2050%3A50,published%20on%2 0Tuesday%20in%20Geneva
3. Timmermans, K. (2023, January 6). Supply chains key to unlocking net zero emissions. Accenture. Retrieved from https://www.accenture.com/usen/insights/supply- chain-operations/supply-chainskey-unlocking-net- zero-emissions
4. NFI Industries. (2021, March 30). Leverage the supply chain to improve customer experience. Retrieved from https://www.nfiindustries.com/aboutnfi/insights/leve rage-the-supply-chain-to-improvecustomer-experience/
5. Burgess, K., Singh, P.J., & Koroglu, R. (2006). Supply chain management: a structured literature review and implications for future research. International Journal of Operations & Production Management, 26(7), 703729. https://doi.org/10.1108/01443570610672202
6. Onfleet, I. (2023, February 8). 7 ways to improve last mile logistics. Delivered Blog. Retrieved from https://onfleet.com/blog/last-mile-logistics/ [Figures 2, 3] Lee, J., & Park, S. (2020).
7. Resource Capacitated Collective Travel Planning in Spatial Databases. IEEE Access, 8, 135443-135457. https://doi.org/10.1109/ACCESS.2020.3011528
8. [8] Porras, C., Fajardo, J., Rosete, A., & Masegosa, A. D. (2021). Partial Evaluation and Efficient Discarding for the Maximal Covering Location Problem. IEEE Access, 9, 20542-20556. https://doi.org/10.1109/ACCESS.2021.3055295