Paper Info
Title
Robust Optimization for Multiobjective Programming Problems with Imprecise Information.
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.
Year
DOI
Venue
2013
10.1016/j.procs.2013.05.046
Procedia Computer Science
Keywords
Field
DocType
Multiobjective Programming,Imprecise Coefficients,Robust Optimization,Interactive Procedures
Mathematical optimization,Robust optimization,Computer science,Multiobjective programming,Linear programming,Artificial intelligence,Machine learning,Decision maker
Conference
Volume
ISSN
Citations 
17
1877-0509
2
PageRank 
References 
Authors
0.39
4
3
Name
Order
Citations
PageRank
Farhad Hassanzadeh1201.75
Hamid R. Nemati2579.72
Minghe Sun335138.27