Otimização do sequenciamento de operações de carga e descarga de caminhões apoiada por algoritmo genético em programação evolutiva

Abstract

Truck sequencing in the loading and unloading operations of multiple products within the downstream segment is a complex logistical problem commonly tackled based on the experience of professionals, with little or no support from a computerized decision support system. This research aims to develop an efficient and feasible solution using Genetic Algorithms, aiming to improve the quality of operational decision-making in this context. The study is justified by the importance of transportation logistics in the supply chain and the challenges faced in determining the ideal mode of transportation for goods. The methodology adopted involved exploratory research of the problem, followed by the modeling of the genetic algorithm, implementation in a computational environment, and validation of the solution in different hypothetical scenarios. The results obtained demonstrated the capability of Genetic Algorithms in optimizing fuel supply and distribution terminal operations, providing decision support in highly dynamic situations. The study's conclusion reaffirms the relevance and effectiveness of Genetic Algorithms as decision support tools for complex logistical problems and suggests further investigations to enhance the proposed solutions and advance knowledge in the field of transportation logistics. This systematic and efficient approach aims to optimize the sequencing of loading and unloading operations of tanker trucks in storage and fuel distribution terminals.