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Conservative linear programming with mixed multiple objectives

Listed author(s):
  • Soyster, AL
  • Lev, B
  • Toof, DI
Registered author(s):

In an ordinary linear program a single objective vector is constructed and one attempts to choose a decision vector to optimize this objective. Often multiple criteria exist or exact estimates for the components of a single objective vector are not entirely clear. For these cases a conservative decision-maker may want to choose an alternative that maximizes the objective value under the worst foreseeable circumstances. Herein we develop a unified framework for applying the maximin criterion to problems with various degrees of uncertainty attached to the objective vector. Three cases are solved via linear programming: (1) Complete Information, (2) Partial Information, and (3) Total Ignorance. It is shown that the functional value of the maximin solution decreases in a convex manner with increasing uncertainty. In addition certain relationships between maximin and efficient solutions are provided. Finally, an extension to integer constrained decision variables is presented.

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Article provided by Elsevier in its journal Omega.

Volume (Year): 5 (1977)
Issue (Month): 2 ()
Pages: 193-205

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Handle: RePEc:eee:jomega:v:5:y:1977:i:2:p:193-205
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