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
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)
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