Applied Mathematics & Information Sciences

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This paper presents a new multi-objective mathematical model for the redundancy allocation problem with the choices of a redundancy strategy and component type in series-parallel systems. The model considers entropy measure which is a measure of uncertainty in the information theory. For the first time, the model maximizes the reliability and entropy of the system and minimizes the nonlinear cost of the system simultaneously. In addition, this paper considers entropy in distribution of the weights of components within subsystems as another form of entropy, which is more realistic than considering entropy in distribution of the number of components. The subsystems can choose a redundancy strategy, which can be active or cold standby, or consider no redundancy. A mathematical compromise programming approach is employed to deal with this problem. As different weights of the objectives and norm of the Lp metric result in various solutions, appropriate criterion is employed to choose the best compromise solution. Finally, the results and conclusion are presented.