A novel strategy for redundant components in reliability--redundancy allocation problems. Issue 11 (1st November 2016)

• Record Type: Journal Article
• Authors: Abouei Ardakan, Mostafa; Sima, Mohammad; Zeinal Hamadani, Ali; Coit, David W.
• Is Part Of: IIE transactions. Volume 48:Issue 11(2016)
• Page Start: 1043
• Page End: 1057
• Publication Date: 2016-11-01
• Subjects: Reliability optimization -- reliability-redundancy allocation problems -- mixed redundancy strategy -- modified version of genetic algorithm; Industrial engineering -- Periodicals; Génie industriel; 620
• DOI: 10.1080/0740817X.2016.1189631
• Languages: English
• ISSNs: 0740-817X

Abstract

ABSTRACT: This article presents a new interpretation and formulation of the Reliability–Redundancy Allocation Problem (RRAP) and demonstrates that solutions to this new problem provide distinct advantages compared with traditional approaches. Using redundant components is a common method to increase the reliability of a system. In order to add the redundant components to a system or a subsystem, there are two traditional types of strategies called active and standby redundancy. Recently a new redundancy strategy, called the "mixed" strategy, has been introduced. It has been proved that in the Redundancy Allocation Problem (RAP), this new strategy has a better performance compared with active and standby strategies alone. In this article, the recently introduced mixed strategy is implemented in the RRAP, which is more complicated than the RAP, and the results of using the mixed strategy are compared with the active and standby strategies. To analyze the performance of the new approach, some benchmark problems on the RRAP are selected and the mixed strategy is used to optimize the system reliability in these situations. Finally, the reliability of benchmark problems with the mixed strategy is compared with the best results of the systems when active or standby strategies are considered. The final results show that the mixed strategy results in an improvement in the reliability of all the benchmark problems and the new strategy outperforms the active and standby strategies in RRAP.