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Energies
Volume 18
Issue 21
10.3390/en18215625
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Energy-Efficient Last-Mile Logistics Using Resistive Grid Path Planning Methodology (RGPPM)

by
Carlos Hernández-Mejía
1,*,
Delia Torres-Muñoz
2,
Carolina Maldonado-Méndez
3,
Sergio Hernández-Méndez
4,
Everardo Inzunza-González
5,
Carlos Sánchez-López
6 and
Enrique Efrén García-Guerrero
5
1
ITS de Misantla, Tecnológico Nacional de México , Misantla 93850, Mexico
2
Instituto Tecnológico Superior de San Martín Texmelucan, San Martín Texmelucan, Puebla 74120, Mexico
3
Ingeniería en Computación, Instituto de Agroingeniería, Universidad del Papaloapan, Loma Bonita 68400, Mexico
4
Artificial Intelligence Research Institute, Universidad Veracruzana, Xalapa 91097, Mexico
5
Facultad de Ingeniería, Arquitectura y Diseño, Universidad Autónoma de Baja California, Carretera Tijuana-Ensenada No. 3917, Ensenada 22860, Mexico
6
Department of Electronics, Autonomous University of Tlaxcala, Clzda Apizaquito S/N, km. 1.5, Apizaco 90300, Mexico
*
Author to whom correspondence should be addressed.
Energies 2025, 18(21), 5625; https://doi.org/10.3390/en18215625 (registering DOI)
Submission received: 16 September 2025 / Revised: 22 October 2025 / Accepted: 23 October 2025 / Published: 26 October 2025
(This article belongs to the Topic AI and Computational Methods for Modelling, Simulations and Optimizing of Advanced Systems: Innovations in Complexity, Second Edition)
Versions Notes

Abstract

Last-mile logistics is a critical operational and environmental challenge in urban areas. This paper introduces an intelligent path planning system using the Resistive Grid Path Planning Methodology (RGPPM) to optimize distribution based on energy and environmental metrics. The foundational innovation is the integration of electrical-circuit analogies, modeling the distribution network as a resistive grid where optimal routes emerge naturally as current flows, offering a paradigm shift from conventional algorithms. Using a multi-connected grid with georeferenced resistances, RGPPM estimates minimum and maximum paths for various starting points and multi-agent scenarios. We introduce five key performance indicators (KPIs)—Percentage of Distance Savings (PDS), Coefficient of Savings (CS), Coefficient of Global Savings (CGS), Percentage of Load Imbalance (PLI), and Percentage of Deviation with Multi-Agent (PDM)—to evaluate system performance. Simulations for textbook delivery to 129 schools in the Veracruz–Boca del Río area show that RGPPM significantly reduces travel distances. This leads to substantial savings in energy consumption, CO2 emissions, and operating costs, particularly with electric vehicles. Finally, the results validate RGPPM as a flexible and scalable strategy for sustainable urban logistics.
Keywords: RGPPM algorithm; path planning methods; georeferenced grid; energy-efficient delivery; multi-agent logistics; carbon emissions reduction RGPPM algorithm; path planning methods; georeferenced grid; energy-efficient delivery; multi-agent logistics; carbon emissions reduction

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MDPI and ACS Style

Hernández-Mejía, C.; Torres-Muñoz, D.; Maldonado-Méndez, C.; Hernández-Méndez, S.; Inzunza-González, E.; Sánchez-López, C.; García-Guerrero, E.E. Energy-Efficient Last-Mile Logistics Using Resistive Grid Path Planning Methodology (RGPPM). Energies 2025, 18, 5625. https://doi.org/10.3390/en18215625

AMA Style

Hernández-Mejía C, Torres-Muñoz D, Maldonado-Méndez C, Hernández-Méndez S, Inzunza-González E, Sánchez-López C, García-Guerrero EE. Energy-Efficient Last-Mile Logistics Using Resistive Grid Path Planning Methodology (RGPPM). Energies. 2025; 18(21):5625. https://doi.org/10.3390/en18215625

Chicago/Turabian Style

Hernández-Mejía, Carlos, Delia Torres-Muñoz, Carolina Maldonado-Méndez, Sergio Hernández-Méndez, Everardo Inzunza-González, Carlos Sánchez-López, and Enrique Efrén García-Guerrero. 2025. "Energy-Efficient Last-Mile Logistics Using Resistive Grid Path Planning Methodology (RGPPM)" Energies 18, no. 21: 5625. https://doi.org/10.3390/en18215625

APA Style

Hernández-Mejía, C., Torres-Muñoz, D., Maldonado-Méndez, C., Hernández-Méndez, S., Inzunza-González, E., Sánchez-López, C., & García-Guerrero, E. E. (2025). Energy-Efficient Last-Mile Logistics Using Resistive Grid Path Planning Methodology (RGPPM). Energies, 18(21), 5625. https://doi.org/10.3390/en18215625

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