Solution approaches for truck routing and scheduling in the forest industry

CORSANO GABRIELA; BORDON MAXIMILIANO RAMON; MONTAGNA JORGE MARCELO

Santiago de Chile

Workshop; Encuentro Latinoamericano de Estudiantes de Doctorado en Modelamiento, Ingeniería y Ciencias, EMIC 2018; 2018

Facultad de Ciencias Físicas y Matemáticas de la Universidad de Chile

Log transportation in forest industry is a resource-intensive operation and represents a great challenge for logistic planners. This operation has the characteristic that a set of harvest areas supplies raw materials to few plants using a significant number of trucks. In general, several trucks make the same route, so it is common queues generation at raw material sites and plants, and therefore, unproductive waiting times. Generally, different types of raw materials are available in the harvest areas, with amounts that far exceed the quantities demanded by plants. Thus, in addition to routing and scheduling decisions, product assignment decisions must also be considered. In the Argentine context, specifically in the Argentinean Northeast (NEA) region, these activities represent the main sustenance of the regional economies, so enhancing efficiency in the transport operation would represent a considerable improvement for these economies.This kind of problems is classified as NP-hard and different approaches are used to deal with it, most of them are heuristic based ((El Hachemi et al., 2013), (Haridass et al., 2014), (Rey et al., 2009), among others). In this work, two solution approaches to solve the log truck routing and scheduling problem based on a previous work developed by Bordón et al. (2018) are presented. The first one involves two stages which are iteratively solved: product allocation, trip composition and truck routing problems are first solved through a Mixed-Integer Linear Programming model (MILP), while in the second stage, fixing the route for each truck according to the results of the previous step, a MILP model for the scheduling of truck arrivals at plants is considered. If no feasible solution for the scheduling problem is obtained, then an integer cut is applied in order to exclude from the search space truck routes already explored in previous iterations. The second methodology is similar to the first one, where actualization of some bounds in each iteration is added, that is, the average routing time and the maximum exceeded route time must be greater than in the previous iteration. This approach defines a heuristic solution, unlike the first methodology in which the problem is solved exactly. The solution approaches are tested in a case study representative of the Argentine context and conclusions are detailed.