Modelo matemático basado en algoritmos genéticos para optimizar las utilidades en una empresa de transporte interprovincial de pasajeros
No Thumbnail Available
Date
2024
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Universidad Nacional de Trujillo
Abstract
La presente investigación tuvo como principal objetivo mejorar las utilidades en una empresa de
transporte interprovincial de pasajeros, habiendo diseñado para ello un modelo de programación
matemática y un modelo de algoritmos genéticos con el propósito de alcanzar soluciones para
una futura optimización de las utilidades de la empresa. El tipo de investigación fue aplicada, la
técnica que se aplicó fue la encuesta y la muestra estuvo conformada por todas las variables de
ingresos, costos y utilidades de una empresa de transporte interprovincial de pasajeros del
territorio peruano. Los resultados comprobaron que la implementación de un modelo matemático
basado en algoritmos genéticos contribuye significativamente en la optimización de las
utilidades en una empresa de transporte interprovincial de pasajeros, visto que se logró
incrementar la utilidad asociada al bus económico (t = 10,375, p < 0,01), al bus cama (t = 29,463,
p < 0,01), al bus mixto (t = 13,590, p < 0,01) y al bus súper cama (t = 5,148, p < 0,01), lográndose
tasa de ocupación óptimas de 63,64%, 98,33%, 78,18% y 86,67%, respectivamente. El modelo
implementado se sustentó en un tamaño de cromosoma de longitud de 19 bits, el tamaño de la
población fue de 10 cromosomas, el método de selección es probabilístico con 4 cromosomas,
cruzamiento con cuatro cromosomas, tipo de cruzamiento multipunto y proceso de mutación a
partir de la segunda iteración de tipo probabilístico.
The main objective of this research was to improve profits in an interprovincial passenger transport company, having designed a mathematical programming model and a genetic algorithm model with the purpose of reaching solutions for a future optimization of the company's profits. The type of research was applied, the technique that was applied was the survey and the sample was made up of all the variables of income, costs and profits of an interprovincial passenger transport company in the Peruvian territory. The results confirmed that the implementation of a mathematical model based on genetic algorithms contributes significantly to the optimization of profits in an interprovincial passenger transport company, since the profit associated with the economic bus was improved (t = 10.375, p < 0.01). , to the sleeper bus (t = 29.463, p < 0.01), to the mixed bus (t = 13.590, p < 0.01) and to the super sleeper bus (t = 5.148, p < 0.01), achieving an optimal occupancy rate of 63,64%, 98,33%, 78,18% and 86,67%, respectively. The implemented model was based on a chromosome size of 19 bits, the population size was 10 chromosomes, the selection method is probabilistic with 4 chromosomes, crossing with four chromosomes, type of multipoint crossing and mutation process a a from the second iteration of probabilistic type.
The main objective of this research was to improve profits in an interprovincial passenger transport company, having designed a mathematical programming model and a genetic algorithm model with the purpose of reaching solutions for a future optimization of the company's profits. The type of research was applied, the technique that was applied was the survey and the sample was made up of all the variables of income, costs and profits of an interprovincial passenger transport company in the Peruvian territory. The results confirmed that the implementation of a mathematical model based on genetic algorithms contributes significantly to the optimization of profits in an interprovincial passenger transport company, since the profit associated with the economic bus was improved (t = 10.375, p < 0.01). , to the sleeper bus (t = 29.463, p < 0.01), to the mixed bus (t = 13.590, p < 0.01) and to the super sleeper bus (t = 5.148, p < 0.01), achieving an optimal occupancy rate of 63,64%, 98,33%, 78,18% and 86,67%, respectively. The implemented model was based on a chromosome size of 19 bits, the population size was 10 chromosomes, the selection method is probabilistic with 4 chromosomes, crossing with four chromosomes, type of multipoint crossing and mutation process a a from the second iteration of probabilistic type.
Description
Keywords
Modelos matemáticos
Optimización de procesos