Fuzzy sets naturally model elastic constraints. Fuzzy constraints satisfaction problem (FCSP) enable the introduction of different kinds of flexibility. Levels of priority can be attached to constraints, and satisfaction levels can be fuzzily thresholded. Fuzzy constraints are aggregated by min operation into a fuzzy set membership function to be maximized (discrimin and leximin refinements of the min ordering can be also used in this maximization). This representation framework, originally expressed in terms of membership functions, is equivalently translated into a set of prioritized crisp constraints, in this paper. We take advantage of this representation for modelling aggregations different from min, expressing either reinforcement and compensation. This offers a logical understanding of fuzzy constraints. In relation to this new representation scheme, computational aspects are briefly exemplified and discussed.
|Title of host publication||1998 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AT THE IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE - PROCEEDINGS|
|Number of pages||6|
|Publication status||Published - 1998|
|Event||IEEE International Conference on Fuzzy Systems at the World Congress on Computational Intelligence (WCCI 98) - Anchorage, United States|
Duration: 4 May 1998 → 9 May 1998
|Conference||IEEE International Conference on Fuzzy Systems at the World Congress on Computational Intelligence (WCCI 98)|
|Period||4/05/98 → 9/05/98|