A Genetic Algorithm Framework for Efficient Electric Patient Transportation
DOI:
https://doi.org/10.61467/2007.1558.2026.v17i5.1328Keywords:
Medical Transportation Optimization, Adaptive Routing Algorithm, Electric Mobility, Patient-Centric Logistic, Electric School Bus, Sustainable Urban Mobility, Genetic Algorithm, optimización del transporte sanitario, algoritmo de enrutamiento adaptativo, movilidad eléctrica, autobús escolar eléctricoAbstract
The transportation of individuals with limited mobility, such as the elderly, persons with disabilities, and pregnant women, to various healthcare facilities for medical appointments poses a significant logistical challenge, particularly in urban areas where mobility is can be complicated by diverse factors. This study proposes the design and implementation of an efficient route planning system that incorporates time window constraints for pick-up, drop-off and travel times for each service requestor, utilizing a fleet of low-capacity electric vehicles. The project merges an insertion heuristic in its first phase to obtain initial solutions with a genetic algorithm in its second phase to refine these solutions, generating feasible and more effective routes. The primary objectives are to minimize the total service time and carbon dioxide emissions while ensuring the satisfaction of patients' specific demands. Several experiments were conducted, varying key system parameters across different scenarios. The results are significant, demonstrating the shortest travel times for each generated route. Furthermore, the findings provide a sustainable alternative that can be replicated in various urban settings.
Spanish-language metadata / Metadatos en español
Título en español:
Marco basado en algoritmos genéticos para el transporte eléctrico eficiente de pacientes
Resumen:
El transporte de personas con movilidad limitada, como adultos mayores, personas con discapacidad y mujeres embarazadas, hacia distintos centros sanitarios para acudir a citas médicas plantea un importante desafío logístico, especialmente en áreas urbanas donde la movilidad puede verse dificultada por diversos factores.
Este estudio propone el diseño y la implementación de un sistema eficiente de planificación de rutas que incorpora restricciones de ventanas de tiempo para la recogida, el traslado, la llegada al destino y los tiempos de viaje correspondientes a cada solicitante del servicio, utilizando una flota de vehículos eléctricos de baja capacidad.
El proyecto combina, en una primera fase, una heurística de inserción para obtener soluciones iniciales y, en una segunda fase, un algoritmo genético para perfeccionarlas, generando rutas factibles y más eficientes. Los principales objetivos son minimizar el tiempo total del servicio y las emisiones de dióxido de carbono, al tiempo que se garantiza la satisfacción de las necesidades específicas de los pacientes.
Se realizaron varios experimentos en los que se modificaron parámetros clave del sistema en distintos escenarios. Los resultados son significativos y muestran los tiempos de viaje más cortos para cada una de las rutas generadas. Además, los hallazgos ofrecen una alternativa sostenible que puede reproducirse en diversos entornos urbanos.
Palabras Claves:
optimización del transporte sanitario, algoritmo de enrutamiento adaptativo, movilidad eléctrica, logística centrada en el paciente, autobús escolar eléctrico, movilidad urbana sostenible, algoritmo genético
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