TY - GEN
T1 - Application of the Linear Model on the Optimal Fleet Calculation for Internal Transportation of a Peruvian University
AU - Agurto-Macazana, Máximo Enrique
AU - Cerquiera-Hoyos, Brenda
AU - Huamani-Ñahui, Cristian Gerardo
AU - Paucar-Martinez, Antonio Pedro
AU - Ninaquispe-Soto, Mario
AU - Riega-Virú, Yasmina
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - The present study focuses on optimizing the internal transportation fleet of a Peruvian university using a linear programming model to adjust the size of the fleet. Through a quantitative and descriptive approach, user data was collected at 10 stops for 30 days, where a linear programming mathematical model was applied to optimize the size of the internal transport fleet, the solution of which was achieved through the use of the Solver add-on Excel. The results indicated that the optimal fleet is 2 units, which improves transportation planning and management, providing a more effective and satisfactory service. The research highlights the need for formal optimization methods to address university-level mobility problems. It demonstrates that route optimization can significantly reduce congestion and improve operational efficiency, contributing to a more sustainable and efficient transport service.
AB - The present study focuses on optimizing the internal transportation fleet of a Peruvian university using a linear programming model to adjust the size of the fleet. Through a quantitative and descriptive approach, user data was collected at 10 stops for 30 days, where a linear programming mathematical model was applied to optimize the size of the internal transport fleet, the solution of which was achieved through the use of the Solver add-on Excel. The results indicated that the optimal fleet is 2 units, which improves transportation planning and management, providing a more effective and satisfactory service. The research highlights the need for formal optimization methods to address university-level mobility problems. It demonstrates that route optimization can significantly reduce congestion and improve operational efficiency, contributing to a more sustainable and efficient transport service.
KW - fleet management
KW - internal transportation
KW - linear programming
KW - Operational efficiency
KW - Route optimization
UR - https://www.scopus.com/pages/publications/105001268133
U2 - 10.1007/978-3-031-83207-9_16
DO - 10.1007/978-3-031-83207-9_16
M3 - Conference contribution
AN - SCOPUS:105001268133
SN - 9783031832062
T3 - Communications in Computer and Information Science
SP - 217
EP - 228
BT - Advanced Research in Technologies, Information, Innovation and Sustainability - 4th International Conference, ARTIIS 2024, Revised Selected Papers
A2 - Guarda, Teresa
A2 - Portela, Filipe
A2 - Gatica, Gustavo
T2 - 4th International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability 2024, ARTIIS 2024
Y2 - 21 October 2024 through 23 October 2024
ER -