Robust optimality analysis of non-degenerate basic feasible solutions in linear programming problems with fuzzy objective coefficients

The necessarily optimal solution is known as the most reasonable solution to linear programming problems with interval/fuzzy objective function coefficients. As it remains optimal against the certain fluctuations of objective function coefficients, the necessarily optimal solution can be seen as a r...

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Bibliographic Details
Published in:Fuzzy optimization and decision making 2023-03, Vol.22 (1), p.51-79
Main Authors: Inuiguchi, Masahiro, Gao, Zhenzhong, Henriques, Carla Oliveira
Format: Article
Language:English
Subjects:
Artificial Intelligence
Calculus of Variations and Optimal Control
Optimization
Coefficients
Decision making
Euclidean space
Fuzzy sets
Linear programming
Mathematical Logic and Foundations
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Probability Theory and Stochastic Processes
Robustness (mathematics)
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Summary:The necessarily optimal solution is known as the most reasonable solution to linear programming problems with interval/fuzzy objective function coefficients. As it remains optimal against the certain fluctuations of objective function coefficients, the necessarily optimal solution can be seen as a robust optimal solution. In this paper, we demonstrate that the necessary optimality degree of a non-degenerate basic feasible solution can be obtained easily by utilizing the tolerance approach. The necessary optimality degree evaluates to what extent the solution remains optimal against the fluctuations of objective function coefficients. Several types of fuzzy subsets showing the possible range of the objective function coefficient vector are considered. For each type of fuzzy subset, an efficient calculation method of necessary optimality degree is proposed. Numerical examples are given to illustrate the proposed methods.
ISSN:1568-4539
1573-2908
DOI:10.1007/s10700-022-09383-2