Abstract
In Constraint Satisfaction and Optimization problems ranging from design engineering to economics, there are often multiple design criteria or cost function that govern the decision whereas, the user needs to be provided with a set of solutions which are the best for all the points of view. In this paper we define a new formalism for multicriteria optimization in constraint satisfaction problems “CSPs” and a multi-agent model solving problems in this setting. This approach separately optimizes different criteria in a distributed way by considering them as cooperative agents trying to reach all the non-dominated solutions. It exploits distributed problems solving together with nogood exchange and negotiation to enhance the overall problem-solving effort. The effectiveness of the approach is discussed on randomly generated examples.
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References
Clearwater, S.H., Huberman, B.A., Hogg, T.: Cooperative problem Solving. In: Huberman, B. (ed.) Computation: The Micro and the View, pp. 33–70 (1992)
Das, I., Dennis, J.E.: Normal boundary intersection. In: WCSMO-2, Proceedings of the Second World Congress of Structural and Multidisciplinary Optimization, pp. 49–54 (1997)
Frost, D.: Algorithms and Heuristics for CSPs. A dissertation Submitted in Partial Satisfaction of the Requirements for the Degree Doctor of Philosophy in Information and Computer Science, University of California, Irvine (1997)
Granvilliers, L., Monfroy, E., Benhamou, F.: Cooperative Solvers in Constraint Programming: a Short Introduction. In: Workshop on Cooperative Solvers in Constraint Programming at the 7th International Conference on Principles and Practice of Constraint Programming (CP 2001), Cyprus (December 2001)
Hogg, T., Williams, P.C.: Solving the really hard problems with cooperative search. In: Hirsh, H., et al. (eds.) AAAI Spring symposium on IA and NP-Hard Problems, pp. 78–84 (1993)
Huberman, B.A.: The performance of cooperative process. Phisica D, pp. 38–47 (1990)
Mackworth, A.: Consistency in networks of relations. Artificial Intelligence (8), 99–118 (1977)
Montanari, U.: Networks of Constraints: fundamental properties and applications to picture processing. Information Sciences (7) (1974)
Sabin, D., Freuder, G.: Contradicting conventional wisdom in Constraint Satisfaction. In: Proceeding of ECAI 1994, pp. 125–129 (1994)
Schiex, T., Verfaillie, G.: Nogood Recording for Static and Dynamic Constraint Satisfaction Problems. In: International Journal of Artificial Intelligence Tools, pp. 187–207 (1994)
Statnikov, R.B., Matusov, J.B.: Multicriteria Optimisation and Engineering. Chapman and Hall, New York (1995)
Othmani, I.: Optimisation Multicritère; Fondements et Concepts, PHD-Thesis, Université Joseph Fourrier, Grenoble (1998)
Tsang, E.: Foundations of Constraint Satisfaction. Academic Press, London (1993)
Tsang, E., Voudouris, C.: Constraint Satisfaction in Discrete Optimisation. In: Unicom Siminar (1998)
Vincke, P.: Multicriteria Decision -Aid. Jhon Wiley & Sons, Chichester (1989)
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Ben Jaâfar, I., Khayati, N., Ghédira, K. (2004). Multicriteria Optimization in CSPs : Foundations and Distributed Solving Approach. In: Bussler, C., Fensel, D. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2004. Lecture Notes in Computer Science(), vol 3192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30106-6_47
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DOI: https://doi.org/10.1007/978-3-540-30106-6_47
Publisher Name: Springer, Berlin, Heidelberg
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