Stackelberg solutions for fuzzy random two-level linear programming through level sets and fractile criterion optimization |
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Authors: | Masatoshi Sakawa Hideki Katagiri |
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Institution: | (1) Faculty of Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima 739-8527, Japan |
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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. |
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Keywords: | |
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