Abstract
Since the early 90’s that Constraint Logic Programming (CLP) has been used to solve Combinatorial Search Problems. Generally, CLP has a good performance with highly constrained problems, but it lacks a “global perspective” of the search space, making the search for the optimal solution more difficult when the problems becomes larger and less constrained. On the other hand, Local Search Methods explore the search space directly through an “intelligent” construction of solution neighbourhoods, turning these methods suitable for solving less constrained and large search spaces problems. The aim of this paper is to present a hybridisation framework that allows combining Local Search methods with Constraint Logic Programming. The first results demonstrate that while maintaining the CLP strengths it is possible to overcome their weaknesses and improve its search efficiency.
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References
Jaffar, J., Lassez, J.: Constraint Logic Programming. In: Proceedings 14th ACM Symposium on Principles of Programming Languages, Munich, Germany, pp. 111–119 (1987)
Harjunkoski, I., Jain, V.: Hybrid mixed-integer/constraint logic programming strategies for solving scheduling and combinatorial optimization problems. Computers and Chemical Engineering 24, 337–343 (2000)
Bockmayr, A., Kasper, T.: Branch-and-Infer: A unifying framework for integer and finite domain constraint programming. INFORMS J. Computing 10, 287–300 (1998)
Thorsteinsson, E.: Branch-and-Check: A Hybrid Framework Integrating Mixed Integer Programming and Constraint Logic Programming. In: Walsh, T. (ed.) CP 2001. LNCS, vol. 2239, p. 16. Springer, Heidelberg (2001)
Codognet, P., Diaz, D.: Yet Another Local Search Method for Constraint Solving. In: Steinhöfel, K. (ed.) SAGA 2001. LNCS, vol. 2264, p. 73. Springer, Heidelberg (2001)
Nareyek, A.: Using Global Constraints for Local Search, Constraint Programming and Large Scale Discrete Optimization. In: DIMACS, vol. 57, pp. 9–28 (2001)
Eugene, C., Rina, D., Matthew, L., Bart, S., Tsang, E.: Systematic Versus Stochastic Constraint Satisfaction. In: IJCAI, pp. 2027-2032 (1995)
Gomes, N., Vale, Z., Ramos, C.: Hybrid Constraint Algorithm for the Maintenance Scheduling of Electric Power Units. In: ISAP 2003, Greece (2003)
Voudouris, C., Tsang, E.P.K.: University of Essex, UK, CSM-247 (August 1995)
Gomes, N., Vale, Z.: Constraint Based Maintenance Scheduling of Electric Power Units. In: Power and Energy Systems (PES 2003), pp. 55–61. Palm Springs, California (2003)
Gomes, N., Vale, Z.: Guided Constraint Search. ISEP, IS2343 (2002)
Wallace, M.: Two Problems - Two Solutions: One System - ECLiPSe. In: IEE Colloquium on Advanced Software Technologies for Scheduling (1993)
Burke, E.S.A.: Hybrid Evolutionary Techniques for the Maintenance Scheduling Problem. IEEE Transactions on Power Systems 15, 122–128 (2000)
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Gomes, N., Vale, Z., Ramos, C. (2003). Reduce and Assign: A Constraint Logic Programming and Local Search Integration Framework to Solve Combinatorial Search Problems. In: Rossi, F. (eds) Principles and Practice of Constraint Programming – CP 2003. CP 2003. Lecture Notes in Computer Science, vol 2833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45193-8_65
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DOI: https://doi.org/10.1007/978-3-540-45193-8_65
Publisher Name: Springer, Berlin, Heidelberg
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