Abstract
The constraint satisfaction problems (CSP) often show great complexity and require a combination of heuristic methods and combinatorial search to be solved in a reasonable time. Therefore, they are of particular importance in the area of intelligent systems. A proposal of a methodology for solving CSP problems is presented, in which the characteristics of combinatorial designs based on algebraic structures, such as Mutually Orthogonal Latin Squares, are exploited in the search for solutions (answers) to a CSP problem. The proposal and the set of heuristics associated with the combinatorial design are evaluated, looking for the pair of heuristics with the best performance in the set of artificial instances of the vehicle routing problem (VRP). The results show the usefulness of the combinatorial designs to find solutions that resolve artificial instances and support the feasibility to extend its application on instances of the state-of-the-art and later on different problem domains.
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Acknowledgements
The authors acknowledge the support provided by the National Council of Science and Technology of Mexico (CONACYT), through the Postgraduate Scholarships: 446105 (J. A. Montesino), 446106 (L.de M. Ortiz) and the Research Grant CÁTEDRAS-2598 (A. Rojas). We also wish to thank the National Technological Institute of Mexico for providing facilities for our Doctoral studies in Computer Sciences (J.A. Montesino and L. de M. Ortiz).
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Montesino-Guerra, J.A., Puga, H., Carpio, J.M., Ornelas-Rodríguez, M., Rojas-Domínguez, A., Ortiz-Aguilar, L. (2020). Combinatorial Designs on Constraint Satisfaction Problem (VRP). In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications. Studies in Computational Intelligence, vol 862. Springer, Cham. https://doi.org/10.1007/978-3-030-35445-9_36
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