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{{short description|Mathematical optimization approach to deal with optimization problems under uncertainty}}
'''Robust fuzzy programming (ROFP)''' is a powerful [[mathematical optimization]] approach to deal with optimization problems under [[uncertainty]]. This approach is firstly introduced at 2012 by Pishvaee, Razmi & Torabi<ref name=":0">{{Cite journal|title = Robust possibilistic programming for socially responsible supply chain network design: A new approach|journal = Fuzzy Sets and Systems|date = 2012-11-01|pages = 1–20|volume = 206|series = Theme : Operational Research|doi = 10.1016/j.fss.2012.04.010|first = M. S.|last = Pishvaee|first2 = J.|last2 = Razmi|first3 = S. A.|last3 = Torabi}}</ref> in the Journal of Fuzzy Sets and Systems. ROFP enables the decision makers to be benefited from the capabilities of both [[fuzzy set|fuzzy]] mathematical programming and [[robust optimization]] approaches. At 2016 Pishvaee and Fazli<ref name=":1">{{Cite journal|title = Novel robust fuzzy mathematical programming methods|journal = Applied Mathematical Modelling|date = 2016-01-01|pages = 407–418|volume = 40|issue = 1|doi = 10.1016/j.apm.2015.04.054|first = Mir Saman|last = Pishvaee|first2 = Mohamadreza|last2 = Fazli Khalaf|doi-access = free}}</ref> 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.
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