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An evolutionary approach to support decision making with linear decision models
Author(s) -
Korhonen Pekka J.,
Narula Subhash C.
Publication year - 1993
Publication title -
journal of multi‐criteria decision analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 47
eISSN - 1099-1360
pISSN - 1057-9214
DOI - 10.1002/mcda.4020020206
Subject(s) - linear programming , computer science , mathematical optimization , decision maker , decision support system , decision analysis , genetic programming , linear fractional programming , linear model , goal programming , mathematics , artificial intelligence , machine learning , operations research , mathematical economics
In this paper we consider decision problems that can be described as linear decision models. These models have been traditionally solved using linear programming, fuzzy linear programming, multiple‐objective linear programming or ‘what‐if’ analysis. Using these approaches, one encounters a number of difficulties. We propose an ‘evolutionary approach’ to overcome these difficulties. In the proposed approach the decision maker does not have to precisely specify the model (i.e. the objective functions, the RHS values, etc.) at the beginning of the solution procedure. In fact, the model evolves as the solution procedure proceeds.