Abstract

In designing phase of systems, design parameters such as component reliabilities and cost are normally under uncer- tainties. Although there have been tremendous advances in the art and science of system evaluation, yet it is very difficult to assess these parameters with a very high accuracy or precision. Therefore, to handle this issue, this paper presents an alternative approach for solving the multi-objective reliability optimization problem by utilizing the uncertain, vague and imprecise data. For this a conflicting nature between the objectives is resolved with the help of intuitionistic fuzzy programming technique by considering the nonlinear degree of membership and non-membership functions. The resultant fuzzy multi-objective optimization problem is converted into single-objective optimization problem using the satisfaction functions with exponential weights. The optimal solution of the corresponding problem has been obtained with the cuckoo search algorithm. Finally, a numerical instance is presented to show the performance of the proposed approach.

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