Artificial intelligence and DOE: an application to school bus routing problems
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© 2019, Springer Science+Business Media, LLC, part of Springer Nature. This paper presents the implementation of simulated annealing (SA) method, an artificial intelligence technique, to solve the optimization problem known as the school bus routing problem (SBRP). A specific challenge in all artificial intelligence optimization techniques is the selection of appropriate value parameters. One contribution of this paper is the implementation of a design of experiments technique to provide statistical support for parameter selection. The SBRP is formulated as a 0¿1 integer linear programming model, where the objective function is to minimize the total cost. Because this problem is combinatorial in nature, it is not possible to find exact solutions in an adequate time, calling for the use of an artificial intelligence optimization technique. The proposed technique is SA due to its modeling flexibility and processing speed. To demonstrate the performance of the proposed algorithm, several experiments with real instances were carried out, showing that the metaheuristic algorithm performs better in quality and time than the classic routing method.
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