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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References
de Castro, L.N.: Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications. Chapman & Hall/CRC (2006)
Hopfield, J.J., Tank, T.W.: “Neural” Computation of Decisions in Optimization Problems. Biological Cybernetics 52(3), 141–152 (1985)
Durbin, R., Willshaw, D.: An Analogue Approach to the Traveling Salesman Problem Using an Elastic Net Method. Nature 326, 689–691 (1987)
Kohonen, T.: Self-Organizing Maps, 3rd edn. Springer, Berlin (2001)
Smith, K.A.: Neural Networks for Combinatorial Optimization: A Review of More than a Decade of Research. INFORMS Journal on Computing 11(1), 15–34 (1999)
Fort, J.C.: Solving a Combinatorial Problem via Self-Organizing Process: An Application of the Kohonen Algorithm to the Traveling Salesman Problem. Biological Cybernetics 59(1), 33–40 (1988)
Angeniol, B., Croix Vaubois, G., Le Texier, J.-Y.: Self-Organizing Feature Maps and the Traveling Salesman Problem. Neural Networks 1, 289–293 (1988)
Somhom, S., Modares, A., Enkawa, T.: A Self-Organising Model for the Travelling Salesman Problem. Journal of the Operational Research Society 48(9), 919–928 (1997)
Cochrane, E.M., Beasley, J.E.: The Co-Adaptive Neural Network Approach to the Euclidean Travelling Salesman Problem. Neural Networks 16(10), 1499–1525 (2003)
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman & Co., New York (1979)
Pasti, R., de Castro, L.N.: A Neuro-Immune Network for Solving the Traveling Salesman Problem. In: International Conference on Neural Networks, pp. 3760–3766 (2006)
Vakhutinsky, A.I., Golden, B.L.: Solving Vehicle Routing Problems Using Elastic Nets. In: IEEE International Conference on Neural Networks, pp. 4535–4540 (1994)
Torki, A., Somhom, S., Enkawa, T.: Competitive Neural Network Algorithm for Solving Vehicle Routing Problem. Computer & Industrial Engineering 33(3-4), 473–476 (1997)
Gomes, L.C.T., Von Zuben, F.J.: Vehicle Routing Based on Self-Organization with and without Fuzzy Inference. In: IEEE International Conference on Fuzzy Systems, pp. 1310–1315 (2002)
de Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer, London (2002)
Masutti, T.A.S., de Castro, L.N.: A Constructive Self-Organizing Network Applied to a Discrete Optimization Problem. In: Seventh International Conference on Intelligent Systems Design and Applications, pp. 52–57 (2007)
Masutti, T.A.S., de Castro, L.N.: Uma Abordagem Neuro-Imune para a Solução do Problema de Múltiplos Caixeiros Viajantes. In: VIII Brazilian Conference on Neural Networks (CD-ROM) (2007)
Christofides, N., Eilon, S.: An Algorithm for the Vehicle Dispatching Problem. Operational Research Quarterly 20(3), 309–318 (1969)
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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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