OPTIMIZATION OF CHANCE CONSTRAINED REDUNDANCY ALLOCATION PROBLEM WITH NON- CRISP COMPONENT RELIABILITIES

In this paper, we have considered the optimal solution of the reliability-redundancy allocation problems (RAP) involving chance constraints in non-crisp environment. The reliabilities of the components are not fixed numbers rather they are non-crisp/imprecise numbers. Also the constraints in the RAP considered are chance constraints which are stochastic in nature. We have proposed a stochastic simulation based Genetic Algorithm approach for solving the reliability optimization problems of the type mentioned in this paper. The impreciseness has been considered in terms of the stochastic approach and the interval approach. In case of the stochastic approach, the reliabilities of the components are taken to be random variables which are distributed normally. After that Monte-Carlo simulation method is used to convert the chance constraints into the deterministic ones. The changed problem is then solved by the real coded genetic algorithm based on stochastic simulation and the constraint handling procedure. Few numerical examples are reported to explain the efficiency of the projected method.

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