Optimization of queuing complexity in the forest transportation problem

Abstract

The need to retain costs is a constant challenge for companies in the forestry sector, both in Brazil and around the world, and one of the factors with the greatest impact on the sector's production costs, without a doubt, is the logistics of forest harvesting and transport. From this perspective, the objective of this work was to evaluate a post-optimized forest transport operational control system using a fuzzy inference system considering real company scenarios in the sector together with a simulation of delays in the system. A classic integer linear programming model and a queue simulator were used to validate the results. The fuzzy model was associated with the queue simulator to provide vehicle rerouting based on queue variables during the operation. The comparison of methods was between the fuzzy model and the queuing simulator without the fuzzy model. Delay times were added to evaluate the adaptability of the methods. The queuing time remained constant with the increase in the delay in the queuing simulator results. The fuzzy model calculated an increase in queue time due to an increase in delay time. The fuzzy model returned plausible results as expected for queuing time behavior when compared with just the queuing simulator. In conclusion, the fuzzy model provides adherence to expert knowledge in queue modeling and provides a better understanding of the forest transport process compared to the queue simulator alone.