A Taylor Series Approach for Solving Linear Fractional Decentralized Bi-Level Multi-Objective Decision-Making Under Fuzziness

This paper presents a Taylor series approach for solving linear fractional decentralized bi-level multi-objective decision-making (LFDBL-MODM) problems with a single decision maker at the upper level and multiple decision makers at the lower level. In the proposed approach, the membership functions associated with each objective(s) of the level(s) of LFDBL-MODM are transformed to a linear form by using a Taylor series and then they are unified. On using the Kuhn-Tucker conditions, the problem is finally reduced to a single objective. Numerical example is given in order to illustrate the efficiency and superiority of the proposed approach.