an availability-based design optimization by using a fuzzy goal programming approach

Selecting systems configuration is a critical step in the safe design of systems. optimizing systems configuration means maximizing their availability and minimizing their overall cost. in this regard, this paper aims to present a novel binary nonlinear fuzzy goal programming (fgp) model to choose components suppliers of multistate parallel series systems based on availability and manufacturing costs. quantity-based discounts, components purchase cost, and penalties for delaying system construction were also considered. in addition, a fuzzy target programming model was applied to minimize deviations from the goal values of expenses. a system reliability block diagram illustrates the system's status. the markov chain model describes a sequence of possible events in which the probability of each event depends on the reliability of system components. the other effect of ordering several pieces from the same supplier is considered (reducing the unit price of elements and increasing their delivery lead time). model results indicate the practical application of this method to optimize system components reliability, taking into account life cycle parameters, including system construction cost and operational reliability.