Journal
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
Volume 50, Issue 6, Pages 915-928Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ijar.2009.02.010
Keywords
Decision under risk; Preference modeling; Aggregation operators; OWA; WOWA; Linear programming
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The problem of averaging outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The so-called Weighted OWA (WOWA) aggregation offers a well-suited approach to this problem. The WOWA aggregation, similar to the classical ordered weighted averaging (OWA). uses the preferential weights assigned to the ordered values (i.e. to the worst value, the second worst and so on) rather than to the specific criteria. This allows one to model various preferences with respect to the risk. Simultaneously, importance weighting of scenarios can be introduced. In this paper, we analyze solution procedures for optimization problems with the WOWA objective functions related to decisions under risk. Linear programming formulations are introduced for optimization of the WOWA objective with monotonic preferential weights thus representing risk averse preferences. Their computational efficiency is demonstrated. (C) 2009 Elsevier Inc. All rights reserved.
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