Authors:
Eduardo A. Alarcón Gerbier
;
Marcela C. Gonzalez-Araya
and
Masly M. Rivera Moraga
Affiliation:
Universidad de Talca, Chile
Keyword(s):
Scheduling, Logistics, Integer Programming, Tomato Industry, Harvest Planning.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
e-Business
;
Enterprise Information Systems
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Logistics
;
Mathematical Modeling
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
Pattern Recognition
;
Scheduling
;
Software Engineering
;
Symbolic Systems
Abstract:
Tomato is a raw material that easily deteriorates once harvested and loaded on trucks, losing juice and flesh.
Therefore, the reduction of trucks’ waiting times in the receiving area of a processing plant can allow reducing
tomato waste. In this article, we develop a model that aims to keep a continuous flow of fresh tomato to a
paste processing plant and to decrease trucks’ waiting times in the plant receiving area. The model is used in
a real case of a tomato paste company. The obtained solutions present a better allocation of the harvest shifts,
allowing more uniform truck arrivals to the plant during the day. Therefore, trucks waiting times are reduced,
decreasing raw material deterioration.