Robust fuzzy programming: Difference between revisions

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{{Orphan|date=June 2016}}

'''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|url = http://www.sciencedirect.com/science/article/pii/S0165011412001819|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|url = http://www.sciencedirect.com/science/article/pii/S0307904X15003686|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}}</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.