A Multilevel Genetic Algorithm for the Maximum Constraint Satisfaction Problem

Author:

Bouhmala Noureddine,Helgen Halvard Sanness,Mathisen Knut Morten

Publisher

Springer International Publishing

Reference20 articles.

1. Bacanin, N., Tuba, M.: Artificial bee colony (ABC) algorithm for constrained optimization improved with genetic operators. Stud. Inf. Control 21(2), 137–146 (2012)

2. Bonyadi, M., Li, X., Michalewicz, Z.: A hybrid particle swarm with velocity mutation for constraint optimization problems. In: Genetic and Evolutionary Computation Conference, pp. 1–8. ACM, New York (2013). ISBN 978-1-4503-1963-8

3. Bouhmala, N.: A variable depth search algorithm for binary constraint satisfaction problems. Math. Prob. Eng. 2015, 10 (2015). doi: 10.1155/2015/637809 . Article ID 637809

4. Curran, D., Freuder, E., Jansen., T.: Incremental evolution of local search heuristics. In: Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation, GECCO 2010, pp. 981–982. ACM, New York (2010)

5. Davenport, A., Tsang, E., Wang, C.J., Zhu, K.: Genet: a connectionist architecture for solving constraint satisfaction problems by iterative improvement. In: Proceedings of the Twelfth National Conference on Artificial Intelligence (1994)

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