Fuzzy global optimization of complex system reliability

In this paper, the problem of optimizing the reliability of complex systems has been modeled as a fuzzy multi-objective optimization problem where apa rt from the system reliability, system cost, weight, and volume are all con sidered as fuzzy goals/objectives. Three different kinds of optimization pr oblems: 1) reliability optimization of a complex system with constraints on cost and weight; 2) optimal redundancy allocation In a multistage mixed sy stem with constraints on cost and weight; and 3) optimal reliability alloca tion in a multistage mixed system with constraints on cost, weight, and vol ume have been solved. Four numerical examples have been solved to demonstra te the effectiveness of the present methodology. The influence of various k inds of aggregators such as: 1) product operator; 2) min operator; 3) the a rithmetic mean operator; 4) fuzzy and 5) a convex combination of the min an d the max operators; and 6) compensatory and (gamma-operator) on the qualit y of the solutions is also studied. The inefficiency of the noncompensatory min operator has been demonstrated. One of the well-known global optimizat ion meta-heuristics-threshold accepting-has been invoked to take care of th e optimization part of the model because it is a variant of the simulated a nnealing algorithm and, hence, can tackle the nonconvex optimization proble ms very well, unlike the modified steepest-ascent method [6], [8], Linear m embership functions have been assumed for the all the goals/objectives, A s oftware has been developed to implement the above model. The results are en couraging because in the case of some problems investigated here they coinc ided with those yielded in the crisp single-objective environment, Also, fu zzy optimization techniques can be used as viable and useful alternatives t o the goal programming approaches for this kind of problems posed in an ill -structured environment.