Robust optimization for interactive multiobjective programming with imprecise information applied to R&D project portfolio selection

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Hamid R. Nemati, Professor (Creator)
The University of North Carolina at Greensboro (UNCG )
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Abstract: A multiobjective binary integer programming model for R&D project portfolio selection with competing objectives is developed when problem coefficients in both objective functions and constraints are uncertain. Robust optimization is used in dealing with uncertainty while an interactive procedure is used in making tradeoffs among the multiple objectives. Robust nondominated solutions are generated by solving the linearized counterpart of the robust augmented weighted Tchebycheff programs. A decision maker’s most preferred solution is identified in the interactive robust weighted Tchebycheff procedure by progressively eliciting and incorporating the decision maker’s preference information into the solution process. An example is presented to illustrate the solution approach and performance. The developed approach can also be applied to general multiobjective mixed integer programming problems.

Additional Information

European Journal of Operational Research, 238(1), 41-53
Language: English
Date: 2014
Multiobjective programming, Robust optimization, Imprecise information, Portfolio selection, Interactive procedures

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