Robust fuzzy programming: Difference between revisions

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'''Robust fuzzy programming (ROFP)''' is a powerful mathematical programming approach to deal with optimization problems under uncertainty. This approach is firstly introduced by Pishvaee, Razmi & Torabi (2012) in the Journal of Fuzzy Sets and Systems. ROFP enables the decision makers to be benefited from the capabilities of both fuzzy mathematical programming and robust optimization approaches. At 2016 Pishvaee and Fazli put a significant step forward by extending the ROFP approach to handle flexibility of constraints and goals.ROFP is able to achieve a robust solution for an optimization problem under uncertainty.
 
ROFP is able to achieve a robust solution for an optimization problem under uncertainty.
=='''Definition of Robust solution''' ==
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'''Definition of Robust solution''' ==
 
Robust solution is defined by Pishvaee and Fazli (2016) as a solution which has "both ''feasibility robustness'' and ''optimality robustness''; Feasibility robustness means that the solution should remain feasible for (almost) all possible values of uncertain parameters and flexibility degrees of constraints and optimality robustness means that the value of objective function for the solution should remain close to optimal value or have minimum (undesirable) deviation from the optimal value for (almost) all possible values of uncertain parameters and flexibility degrees on target value of goals".