Abstract
In this article, assuming non-cooperative behaviour of the decision makers, solution methods for decision making problems in hierarchical organizations under fuzzy random environments are presented. Taking into account hte vagueness of judgments by decision makers, fuzzy goals are introduced into the formulated fuzzy random two-level linear programming problems. Considering the possibility and necessity measures that each objective function fulfils the corresponding fuzzy goal, the fuzzy random two-level linear programming problems to minimize each objective function with fuzzy random variables are transformed into stochastic two-level programming problems to maximize the degree of possibility and necessity that each fuzzy goal is fulfilled. Through the fractile criterion optimization model, or Kataoka's model in stochastic programming, the transformed stochastic two-level programming problems can be reduced to deterministic two-level programming problems. For the transformed problems, extended concepts of Stackelberg solutions are introduced and computational methods are also presented. A numerical example is provided to illustrate the proposed methods.
Published Version
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