Robust Optimization for Multiobjective Programming Problems with Imprecise Information

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Hamid R. Nemati, Associate Professor (Creator)
Institution
The University of North Carolina at Greensboro (UNCG )
Web Site: http://library.uncg.edu/

Abstract: A robust optimization approach is proposed for generating nondominated robust solutions for multiobjective linear programming problems with imprecise coefficients in the objective functions and constraints. Robust optimization is used in dealing with impreciseness while an interactive procedure is used in eliciting preference information from the decision maker and in making tradeoffs among the multiple objectives. Robust augmented weighted Tchebycheff programs are formulated from the multiobjective linear programming model using the concept of budget of uncertainty. A linear counterpart of the robust augmented weighted Tchebycheff program is derived. Robust nondominated solutions are generated by solving the linearized counterpart of the robust augmented weighted Tchebycheff programs.

Additional Information

Publication
Procedia Computer Science, 17, 357-364.
Language: English
Date: 2013
Keywords
Multiobjective Programming, Imprecise Coefficients, Robust Optimization, Interactive Procedures

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