Abstract
Some features of a large number of combinatorial optimization problems prevent the use of exact solution methods, thus requiring the application of heuristic techniques to find good solutions, not always the optimal ones, in a feasible amount of time. This paper describes a heuristic approach, which is a hybrid between artificial neural networks and artificial immune systems, to solve the capacitated vehicle routing problem. This algorithm is based on a competitive model, which does not use a cost or evaluation function to determine the quality of the solution proposed. Despite this apparent drawback, the set of tests conducted with the proposed approach indicates a good performance of the algorithm when compared with similar works from the literature and the known best solutions available.
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Masutti, T.A.S., de Castro, L.N. (2008). A Neuro-Immune Algorithm to Solve the Capacitated Vehicle Routing Problem. In: Bentley, P.J., Lee, D., Jung, S. (eds) Artificial Immune Systems. ICARIS 2008. Lecture Notes in Computer Science, vol 5132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85072-4_19
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DOI: https://doi.org/10.1007/978-3-540-85072-4_19
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