Integrated Allocation of Gasoline Stations and Bio-gasoline Facilities: A Logistical Approach for Sustainable Gasoline Distribution in Mexico

Authors

  • Santiago Omar Caballero Morales Universidad Popular Autonoma del Estado de Puebla
  • Gladys Bonilla-Enriquez Tecnologico Nacional de Mexico TECNM / Instituto Tecnológico de Puebla ITP
  • Felipe-de-Jesus Trujillo-Romero Universidad de Guanajuato - Department of Engineering in Electronics

DOI:

https://doi.org/10.61467/2007.1558.2025.v16i3.608

Keywords:

Gasoline Distribution, Biofuel Plants, k-Means Algorithm

Abstract

Optimizing the allocation of gasoline stations to refineries and depots enhances service coverage and response times, particularly during contingencies. Integrating biofuel production facilities supports sustainable energy initiatives and fuel supply. This study formulates an approach to optimize the allocation of gasoline stations to existing production and storage facilities while planning for bio-diesel plant expansion. It considers geographic distribution, balanced load allocation, minimal distances, and expansion costs. Using accurate data from Mexico, an extended k-means algorithm was developed to address the location/allocation problem involving gasoline stations, refineries, depots, and future biofuel facilities. Results demonstrate that additional biofuel facilities can alleviate service loads on existing infrastructure while enhancing sustainability and reducing environmental impact. These findings provide valuable insights for policymakers and urban planners aiming to improve fuel distribution networks and promote sustainable energy solutions.

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Published

2025-07-14

How to Cite

Caballero Morales, S. O., Bonilla-Enriquez, G., & Trujillo-Romero, F.- de-J. (2025). Integrated Allocation of Gasoline Stations and Bio-gasoline Facilities: A Logistical Approach for Sustainable Gasoline Distribution in Mexico. International Journal of Combinatorial Optimization Problems and Informatics, 16(3), 216–228. https://doi.org/10.61467/2007.1558.2025.v16i3.608

Issue

Section

Recent Advances on Soft Computing