INVESTIGADORES
RODRIGUEZ Maria Analia
artículos
Título:
Generalized disjunctive programming models for the truck loading problem: a case study from the non-alcoholic beverages industry
Autor/es:
JUAN MATIAS NOVAS; JUAN IGNACIO RAMELLO; RODRIGUEZ, MARIA ANALIA
Revista:
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
Editorial:
PERGAMON-ELSEVIER SCIENCE LTD
Referencias:
Lugar: Amsterdam; Año: 2020
ISSN:
1366-5545
Resumen:
A real-world truck loading problem is considered for the major non-alcoholic beverages bottler in Argentina. The previous manual procedure to define the truck loading plan is improved by automatizing the process through a set of optimization models applying Generalized Disjunctive Programming. Most of the operational practices and restrictions are taken into account. Given that there is flexibility to load products in the trucks, a better use of their capacities is obtained and the balance of forces addressed avoids expensive penalties fees. By a set of examples, different metrics are tested and good quality results are obtained for an every-day practice.
