A new interactive approach to solve entropy based fuzzy reliability optimization model

In this paper, we proposed the problem of optimizing the reliability of a series–parallel system in fuzzy environment and also consider entropy as an additional objective function. Taking into account the resources (such as weight, volume, cost etc.) as generalized trapezoidal fuzzy number and considering vagueness of judgements of the decision maker, an Interactive fuzzy multiple-objective decision making method is presented to solve the above mentioned reliability optimization problem based on entropy. An important characteristics of the Interactive approach is that, it provides a learning process about the system, whereby the decision maker can learn to recognize good solutions, relative importance of factors in the system and then, design a high productivity system instead of optimizing a given system. The object of this study is to find the optimum number of redundant components of the proposed entropy based reliability optimization problem to produce highly reliable system as well as maximize the entropy amount of the system subject to the available resources of each component. Here total integral value of fuzzy number is used to transform the fuzzy problem into crisp multi-objective problem. The effectiveness of additional entropy to this model and the performance of this solution approach are evaluated by comparing its result with the other method at the end of this paper.