Open AccessVEHICLE ASSIGNMENT WITH PENALTY COSTS: A CASE OF MEXICAN FREIGHT TRANSPORT
Author(s) -
Felix Eduardo Bueno-Pascual,
José Luis Martínez-Flores,
Diana SánchezPartida,
Patricia CanoOlivos
Publication year - 2022
Publication title -
acta logistica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.205
H-Index - 3
ISSN - 1339-5629
DOI - 10.22306/al.v9i1.272
Subject(s) - truck , license , transport engineering , revenue , cost reduction , operations research , market share , total cost , business , operations management , computer science , engineering , finance , marketing , automotive engineering , accounting , operating system
The reduction of logistics costs is very important for Mexican companies, especially for those from freight transport industry. They must manage their operations efficiently and effectively to increase the revenue, which is reduced if trucks are not being productive. The objective of this research is to provide a model for a Mexican freight transport company, which lets the company reduce transportation costs, based on assignment models to make daily assignment programme of trucks. One particularity of the model being built is the fact that it will not only include general costs as in a Generalised Assignment Procedure (GAP), but also penalty costs caused by truck drivers. The main problem consisted in minimize the total cost of assigning 100 vehicles owned by the company to 10 routes (in which it was required to be transported molasse, and sand), considering that trucks cannot be assigned to some routes due to their characteristics, as well as they must assign different operators to the routes (which are classified as A, B, and C, depending on the characteristics like license type, performance, among others); thus, it was able to assign 100 operators with different characteristics to 100 different units required in 10 routes to satisfy market demands, achieving a reduction about 44.11% of current costs related to assignment, maintenance, idle time, penalty, and logistics costs.