Abstract
We present Branch-and-Check, a hybrid framework integrating Mixed Integer Programming and Constraint Logic Programming, which encapsulates the traditional Benders Decomposition and Branch-and-Bound as special cases. In particular we describe its relation to Benders and the use of nogoods and linear relaxations.We give two examples of how problems can be modelled and solved using Branch-and-Check and present computational results demonstrating more than order-of-magnitude speedup compared to previous approaches.We also mention important future research issues such as hierarchical, dynamic and adjustable linear relaxations.
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References
J. F. Benders. Partitioning procedures for solving mixed-variables programming problems. Numer. Math., 4:238–252, 1962.
H. Beringer and B. De Backer. Combinatorial problem solving in constraint logic programming with cooperating solvers. In C. Beierle and L. Plümer, editors, Logic Programming: Formal Methods and Practical Applications, Studies in Computer Science and Artificial Intelligence, chapter 8, pages 245–272. Elsevier, 1995.
A. Bockmayr and T. Kasper. Branch-and-infer: A unifying framework for integer and finite domain constraint programming. INFORMS Journal on Computing, 10(3):287–300, 1998.
K. Darby-Dowman and J. Little. The significance of constraint logic programming to operational research. Operational Research Tutorial Papers, pages 20–45, 1995.
K. Darby-Dowman and J. Little. Properties of some combinatorial optimization problems and their effect on the performance of integer programming and constraint logic programming. INFORMS Journal on Computing, 10(3):276–286, Summer 1998.
I. R. de Farias, E. L. Johnson, and G. L. Nemhauser. A branch-and-cut approach without binary variables to combinatorial optimization problems with continuous variables and combinatorial constraints. Knowledge Engineering Review, special issue on AI/OR, submitted, 1999.
F. Focacci, A. Lodi, and M. Milano. Cutting planes in constraint programming: An hybrid approach. In CP-AI-OR’00Workshop on Integration of AI and OR techniques in Constraint Programming for Combinatorial Optimization Problems, March 2000.
A. M. Geoffrion. Generalized Benders decomposition. Journal of Optimization theory and Applications, 10:237–260, 1972.
I. Harjunkoski, V. Jain, and I. E. Grossmann. Hybrid mixed-integer/constraint logic programming strategies for solving scheduling and combinatorial optimization problems. Computers and Chemical Engineering, 24:337–343, 2000.
J. N. Hooker. Logic-based methods for optimization. In Alan Borning, editor, Principles and Practice of Constraint Programming, volume 874 of Lecture Notes in Computer Science. Springer, May 1994. (PPCP’94: Second International Workshop, Orcas Island, Seattle, USA).
J. N. Hooker. Logic-Based Methods for Optimization. Wiley, NewYork, 2000.
J. N. Hooker and M. A. Osorio. Mixed logical/linear programming. Discrete Applied Mathematics, 96–97(1–3):395–442, 1999.
John N. Hooker, Hak-Jin Kim, and Greger Ottosson. A declarative modeling framework that integrates solution methods. Annals of Operations Research, Special Issue on Modeling Languages and Approaches, to appear, 1998.
John N. Hooker and Greger Ottosson. Logic-based Benders decomposition. Mathematical Programming, 2000. Submitted.
John N. Hooker, Greger Ottosson, Erlendur S. Thorsteinsson, and Hak-Jin Kim. On integrating constraint propagation and linear programming for combinatorial optimization. In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), pages 136–141. AAAI, The AAAI Press/The MIT Press, July 1999.
John N. Hooker, Greger Ottosson, Erlendur S. Thorsteinsson, and Hak-Jin Kim. Ascheme for unifying optimization and constraint satisfaction methods. Knowledge Engineering Review, Special Issue on Artifical Intelligence and Operations Research, 15(1):11–30, 2000.
John N. Hooker and Hong Yan. Logic circuit verification by Benders decomposition. In V. Saraswat and P. Van Hentenryck, editors, Principles and Practice of Constraint Programming: The Newport Papers, pages 267–288. MIT Press, 1995.
V. Jain and I. E. Grossmann. Algorithms for hybrid MILP/CP models for a class of optimization problems. INFORMS, 2000. Presented at INFORMS Salt Lake City, paper SD32.1.
R. G. Jeroslow and J. Wang. Dynamic programming, integral polyhedra, and horn clause knowledge bases. ORSA Journal on Computing, 1(1):7–19, 1988.
Michela Milano, Greger Ottosson, Philippe Refalo, and Erlendur S. Thorsteinsson. Global constraints: When constraint programming meets operation research. INFORMS Journal on Computing, Special Issue on the Merging of Mathematical Programming and Constraint Programming, March 2001. Submitted.
Greger Ottosson, Erlendur S. Thorsteinsson, and John N. Hooker. Mixed global constraints and inference in hybrid CLP-IP solvers. Annals of Mathematics and Artificial Intelligence, Special Issue on Large Scale Combinatorial Optimisation and Constraints, March 2001. Accepted for publication.
Philippe Refalo. Tight cooperation and its application in piecewise linear optimization. In Joxan Jaffar, editor, Principles and Practice of Constraint Programming, volume 1713 of Lecture Notes in Computer Science. Springer, October 1999.
Robert Rodošek, Mark Wallace, and Mozafar Hajian. A new approach to integrating mixed integer programming and constraint logic programming. Annals of Operations Research, Advances in Combinatorial Optimization, 86:63–87, 1999.
Erlendur S. Thorsteinsson and Greger Ottosson. Linear relaxations and reduced-cost based propagation of continuous variable subscripts. Annals of Operations Research, Special Issue on Integration of Constraint Programming, Artificial Intelligence and Operations Research Methods, January 2001. Submitted.
P. Van Hentenryck. The OPL Optimization Programming Language. MIT Press, 1999.
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Thorsteinsson, E.S. (2001). Branch-and-Check: A Hybrid Framework Integrating Mixed Integer Programming and Constraint Logic Programming. In: Walsh, T. (eds) Principles and Practice of Constraint Programming — CP 2001. CP 2001. Lecture Notes in Computer Science, vol 2239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45578-7_2
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DOI: https://doi.org/10.1007/3-540-45578-7_2
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