Abstract
This paper presents a Fuzzy Mathematical Programming (FMP) approach for solving Multilevel Decentralized Programming Problems (ML(D)PPs). The higher level Decision Maker(DM) makes the decision first to provide preferred values of the decision variables under control and the follower reacts by optimizing the objective function conditioned on the higher level DM’s decision. A simple method is employed to find a satisfactory solution under fuzziness with linear fractional objectives overcoming the selection of membership functions and tolerance values and terminates in a finite number of steps. The methodology proposes small number of iterations and aims at reducing the feasible space of a decision variable at each level of the hierarchical system until a satisfactory solution is obtained at the last level. The Stackelberg strategy is employed as a solution concept when decision problems are modeled as two-level programming problems, whether there is a cooperative relationship between the decision makers or not. Illustrative numerical example is provided to demonstrate the feasibility of the proposed method.
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