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Abstract
The Constraint Hierarchy (CH) framework is used to tacklemultiple criteria selection (MCS), consisting of a set of candidates and a set of, possibly competing, criteria for selecting the ”best“ candidate(s). In this paper, we identify aspects of the CH framework for further enancement so as to model and solve MCS problems more accurately. We propose the Fuzzy Constraint Hierarchies framework, which allows constraints to belong to, possibly, more than one level in a constraint hierarchy to a varying degree. We also propose to replace the standard equality relation = used in valuation comparators of the CH framework by the α-approximate equality relation =a(α) for providing more flexible control over the handling of valuations with close error values. These proposals result in three new classes of valuation comparators. Formal properties of the new comparators are given, wherever possible.
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References
S. Bistarelli, U. Montanari, and F. Rossi. Semiring-based constraint solving and optimization.Journal of the ACM, 44(2):201–236, 1997.
A. Borning, B. Freeman-Benson, and M. Wilson. Constraint hierarchies.Lisp and Symbolic Computation, 5(3):223–270, 1992.
M. Jampel. A brief overview of over-constrained systems. In M. Jampel, E. Freuder, and M. Maher, editors,Over-Constrained Systems, pages 1–22. LNCS 1106, Springer-Verlag, 1996.
G.J. Klir and T.A. Folger.Fuzzy Sets, Uncertainty, and Information. Prentice Hall, 1992.
F. Rossi and A. Sperduti. Learning solution preferences in constraint problems.Journal of Theoretical and Experimental Artificial Intelligence, 10, 1998.
Marc Roubens. Fuzzy sets and decision analysis.Fuzzy Sets and Systems, 90(2):199–206, 1997.
Wolfgang Slany. Scheduling as a fuzzy multiple criteria optimization problem.Fuzzy Sets and Systems, 78:197–222, 1996.
M. Tamiz, editor.Multi-objective programming and goal programming: theories and applications. LNEMS 432, Springer-Verlag, 1996.
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Authors and Affiliations
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shantin, N.T, Hong Kong, China
R. W. L. Kam & J. H. M. Lee
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Editors and Affiliations
School of Computing and Information Technology, Griffith University, Nathan, Queensland, 4111, Australia
Michael Maher
ILOG S.A., 9, rue de Verdun, BP 85, F-94253, Gentilly Cedex, France
Jean-Francois Puget
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© 1998 Springer-Verlag Berlin Heidelberg
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Kam, R.W.L., Lee, J.H.M. (1998). Fuzzifying the Constraint Hierarchies Framework. In: Maher, M., Puget, JF. (eds) Principles and Practice of Constraint Programming — CP98. CP 1998. Lecture Notes in Computer Science, vol 1520. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49481-2_21
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