SUMMARY
Arising from research in the computer science community, constraint programming is a relatively new technique for solving optimization problems. It often is applied to difficult combinatorial optimization problems arising in configuration, sequencing, and scheduling. To apply constraint programming, users must write software that includes both a model of an optimization problem plus an algorithmic search procedure that indicates how to search for a solution.
BACKGROUND
Constraint programming is often called constraint logic programming, and originates in the artificial intelligence literature in the computer science community. Here, the word “programming” refers to computer programming. Knuth (1968)defines a computer program as “an expression of a computational method in a computer language.” A computer program can be viewed as a plan of action of operations of the computer, and hence the common concept of a “plan” is shared with the origins of linear programming. With...
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References
Caseau, Y. and Laburthe, F. (1995). The Claire documentation, LIENS Report 96–15, Ecole Normale Superieure, Paris.
Colmerauer, A. (1990). “An introduction to PROLOG III,” Communications of the ACM 33(7), 70–90.
Dincbas, M., Van Hentenryck, P., Simonis, H., Aggoun, A., Graf, T., and Berthier, F. (1988). “The Constraint Logic Programming Language CHIP,” Proceedings of the International Conference on Fifth Generation Computer Systems, Tokyo, Japan, December.
Garfinkel, R. S. and Nemhauser, G. L. (1972). Integer Programming, John Wiley, New York.
Harvey, W. D. and Ginsberg, M. L. (1995). “Limited Discrepancy Search,” Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), volume 1, 607–613.
ILOG (1999). ILOG Solver 4.4 Users Manual, ILOG, Gentilly, France.
Jaffar, J. and Lassez, J.-L. (1987). “Constraint Logic Programming,” Conference Record of the Fourteenth Annual ACM Symposium on Principles of Programming Languages, Munich, 111–119.
Knuth, D. E. (1968). Fundamental Algorithms, The Art of Computer Programming, Volume 1, 2nd ed., Addison-Wesley, Reading, Massachusetts.
Lauriere, J.-L. (1978). “A Language and a Program for Stating and Solving Combinatorial Problems,” Artificial Intelligence 10, 29–127.
Lawler, E. L. and Wood, D. E. (1966). “Branch-and-Bound Methods: A Survey,” Operations Research 14, 699–719.
Mackworth, A. K. (1977). “Consistency in networks of relations,” Artificial Intelligence 8, 99–118.
Meseguer, P. (1997). “Interleaved Depth-First Search,” Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), volume 2, 1382–1387.
Nilsson, N. J. (1971). Problem Solving Methods in Artificial Intelligence, McGraw-Hill, New York.
Puget, J.-F. (1992). “Pecos: a High Level Constraint programming Language,” in Proceedings of the 1st Singapore Intl. Conf. on Intelligent Systems.
Puget, J.-F. (1994). “A C++ Implementation of CLP,” Proceedings of the 2nd Singapore Intl. Conf. on Intelligent Systems. (See also the current web site http://www.ilog.com/products/optimization/research/spicis94_OnlinePDF.pdf.)
Smolka, G. (1995). “The Oz Programming Model,” in Computer Science Today, J. van Leeuwen, ed., Lecture Notes in Computer Science 1000, Springer-Verlag, 324–343.
Van Hentenryck, P. (1989). Constraint Satisfaction in Logic Programming, MIT Press, Cambridge, Massachusetts.
Van Hentenryck, P. (1999). The OPL Optimization Programming Language, MIT Press, Cambridge, Massachusetts.
Van Hentenryck, P., Deville, Y., and Teng, C. M. (1992). “A generic arc-consistency algorithm and its specializations,” Artificial Intelligence 57, 291.
Walsh, T. (1997). “Depth-bounded discrepancy search,” Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), volume 2, 1388–1395.
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© 2001 Kluwer Academic Publishers
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Lustig, I., Puget, JF. (2001). Constraint programming . In: Gass, S.I., Harris, C.M. (eds) Encyclopedia of Operations Research and Management Science. Springer, New York, NY. https://doi.org/10.1007/1-4020-0611-X_157
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DOI: https://doi.org/10.1007/1-4020-0611-X_157
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