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Published in:
2009 | OriginalPaper | Chapter
Interactive Robust Multiobjective Optimization Driven by Decision Rule Preference Model
Author : Roman Słowiński
Published in: Modeling Decisions for Artificial Intelligence
Publisher: Springer Berlin Heidelberg
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Interactive procedures for MultiObjective Optimization (MOO) consist of a sequence of steps alternating calculation of a sample of non-dominated solutions and elicitation of preference information from the Decision Maker (DM). We consider
three types of procedures
, where in preference elicitation stage, the DM is just asked to indicate which solutions are relatively good in the proposed sample. In all three cases, the preference model is a set of “if . . . , then . . .” decision rules inferred from the preference information using the Dominance-based Rough Set Approach (DRSA) (3; 4; 11).