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Stackelberg solutions for fuzzy random two-level linear programming through level sets and fractile criterion optimization

Masatoshi Sakawa () and Hideki Katagiri ()

Central European Journal of Operations Research, 2012, vol. 20, issue 1, 101-117

Abstract: This paper considers Stackelberg solutions for two-level linear programming problems under fuzzy random environments. To deal with the formulated fuzzy random two-level linear programming problem, an α-stochastic two-level linear programming problem is defined through the introduction of α-level sets of fuzzy random variables. Taking into account vagueness of judgments of decision makers, fuzzy goals are introduced and the α-stochastic two-level linear programming problem is transformed into the problem to maximize the satisfaction degree for each fuzzy goal. Through fractile criterion optimization in stochastic programming, the transformed stochastic two-level programming problem can be reduced to a deterministic two-level programming problem. An extended concept of Stackelberg solution is introduced and a numerical example is provided to illustrate the proposed method. Copyright Springer-Verlag 2012

Keywords: Two-level linear programming; Fuzzy random variables; Stackelberg solutions; Level sets; Fractile criterion optimization (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/s10100-010-0156-5

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