Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 174, Issue 3, Pages 1353-1367Publisher
ELSEVIER
DOI: 10.1016/j.ejor.2005.07.019
Keywords
fuzziness; randomness; fuzzy random variable; linear programming
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In many real-life problems one has to base decision on information which is both fuzzily imprecise and probabilistically uncertain. Although consistency indexes providing a union nexus between possibilistic and probabilistic representation of uncertainty exist, there are no reliable transformations between them. This calls for new paradigms for incorporating the two kinds of uncertainty into mathematical models. Fuzzy stochastic linear programming is an attempt to fulfill this need. It deals with modelling and problem solving issues related to situations where randomness and fuzziness co-occur in a linear programming framework. In this paper we provide a survey of the essential elements, methods and algorithms for this class of linear programming problems along with promising research directions. Being a survey, the paper includes many references to both give due credit to. results in the field and to help readers obtain more detailed information on issues of interest. (c) 2005 Elsevier B.V. All rights reserved.
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