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Optimization of Reliability–Redundancy Allocation Problems: A Review of the Evolutionary Algorithms

Haykel Marouani1,2, Omar Al-mutiri1,*

1 College of Engineering, Muzahimiyah Branch, King Saud University, Riyadh, 11451, Saudi Arabia
2 University of Monastir, LGM, ENIM, Avenue Ibn-Eljazzar, 5019, Monastir, Tunisia

* Corresponding Author: Omar Al-mutiri. Email: email

Computers, Materials & Continua 2022, 71(1), 537-571.


The study of optimization methods for reliability–redundancy allocation problems is a constantly changing field. New algorithms are continually being designed on the basis of observations of nature, wildlife, and humanity. In this paper, we review eight major evolutionary algorithms that emulate the behavior of civilization, ants, bees, fishes, and birds (i.e., genetic algorithms, bee colony optimization, simulated annealing, particle swarm optimization, biogeography-based optimization, artificial immune system optimization, cuckoo algorithm and imperialist competitive algorithm). We evaluate the mathematical formulations and pseudo-codes of each algorithm and discuss how these apply to reliability–redundancy allocation problems. Results from a literature survey show the best results found for series, series–parallel, bridge, and applied case problems (e.g., overspeeding gas turbine benchmark). Review of literature from recent years indicates an extensive improvement in the algorithm reliability performance. However, this improvement has been difficult to achieve for high-reliability applications. Insights and future challenges in reliability–redundancy allocation problems optimization are also discussed in this paper.


Cite This Article

H. Marouani and O. Al-mutiri, "Optimization of reliability–redundancy allocation problems: a review of the evolutionary algorithms," Computers, Materials & Continua, vol. 71, no.1, pp. 537–571, 2022.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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