Abstract
The study objective was to evaluate the performance of SAGAC in optimizing a linear mathematical model in whole variables to determine the most cost-effective solution in transporting cattle for slaughter. The model determines the choice of refrigerator truck, road (route), and an open-truck in a scripting process. The tests performed with the SAGAC algorithm for optimizing the proposed model were compared with the results obtained, under similar conditions, by the branch-and-bound method for solving entire problems and solving a problem optimally. After the first twenty-two experimental trials, for comparison between the two methods, nine more experimental trials were carried out, with an increase in the degree of complexity, only with the SAGAC algorithm. The results obtained in the first twenty-two experimental trials demonstrate an equivalent performance between the two methods, showing that the SAGAC algorithm, even though it is not a technique that guarantees optimal results, in this case, was also able to find them. The nine final experiments performed only by SAGAC showed satisfactory results, with an evolutionary curve of exponential behavior.
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The first author wishes to thank the Coordination of Superior Studies (Capes) for the scholarship.
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Benvenga, M.A.C., de Alencar Nääs, I. (2021). Application of Hybrid Metaheuristic Optimization Algorithm (SAGAC) in Beef Cattle Logistics. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 631. Springer, Cham. https://doi.org/10.1007/978-3-030-85902-2_62
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