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A heuristic survival signature based approach for reliability-redundancy allocation.

Huang, X. and Coolen, F.P.A. and Coolen-Maturi, T. (2019) 'A heuristic survival signature based approach for reliability-redundancy allocation.', Reliability engineering & system safety., 185 . pp. 511-517.


In recent research, the major focus on reliability-redundancy allocation problems has been on the possibility of using more efficient and effective algorithms to improve convergence speed and solution accuracy of the optimization model. But the model of reliability-redundancy allocation itself has not been investigated further. In this paper, we try to simplify the optimization model of the reliability-redundancy allocation problem by using the theory of survival signature. To achieve this, the information of the structure of a system is summarized by the survival signature. The reliability-redundancy allocation problem is formulated as an optimization problem with the objective of maximizing system reliability under some constraints. A new adaptive penalty function is proposed to transfer the constraint optimization problem to an unconstraint one. Then a heuristic algorithm called stochastic fractal search is applied to solve the unconstraint optimization. Moreover, the (joint) structure importance is used to measure the relative importance of components to concretely allocate the redundancy level of each component. The proposed method only needs to calculate the survival signature once, reduces the dimension of the optimization problem and provides insight into system reliability-redundancy allocation.

Item Type:Article
Full text:Publisher-imposed embargo
(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
File format - PDF
Publisher Web site:
Publisher statement:© 2019 This manuscript version is made available under the CC-BY-NC-ND 4.0 license
Date accepted:01 February 2019
Date deposited:05 February 2019
Date of first online publication:02 February 2019
Date first made open access:02 February 2020

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