Abstract
Constraint Satisfaction Problems (CSP) provide a modelling framework for many computer aided decision making problems. Many of these problems are associated to an optimization criterion. Solving a CSP consists in finding an assignment of values to the variables that satisfies the constraints and optimizes a given objective function (in case of an optimization problem). In this paper, we extend our framework for genetic algorithms (GA) as suggested by the reviewers of our previous ICLP paper [5]. Our purpose is not to solve efficiently the Balanced Academic Curriculum Problem (BACP) [2] but to combine a genetic algorithm with constraint programming techniques and to propose a general modelling framework to precisely design such hybrid resolution process and highlight their characteristics and properties.
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References
Apt, K.R.: From chaotic iteration to constraint propagation. In: Proceedings of ICALP 1997, pp. 36–55. Springer, Heidelberg (1997)
Castro, C., Manzano, S.: Variable and value ordering when solving balanced academic curriculum problems. In: Proceedings of 6th Workshop of the ERCIM WG on Constraints. CoRR cs.PL/0110007 (2001)
Gent, I., Walsh, T., Selman, B.: funded by the UK Network of Constraints, http://www.csplib.org
Holland, J.H.: Adaptation in Natural and Artificial Systems (1975)
Monfroy, E., Saubion, F., Lambert, T.: On hybridization of local search and constraint propagation. In: Demoen, B., Lifschitz, V. (eds.) ICLP 2004. LNCS, vol. 3132, pp. 299–313. Springer, Heidelberg (2004)
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Lambert, T., Castro, C., Monfroy, E., Riff, M.C., Saubion, F. (2005). Hybridization of Genetic Algorithms and Constraint Propagation for the BACP. In: Gabbrielli, M., Gupta, G. (eds) Logic Programming. ICLP 2005. Lecture Notes in Computer Science, vol 3668. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562931_38
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DOI: https://doi.org/10.1007/11562931_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29208-1
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