EconPapers    
Economics at your fingertips  
 

Water cycle algorithm for solving the reliability-redundancy allocation problem with a choice of redundancy strategies

Narges Mahdavi-Nasab, Mostafa Abouei Ardakan and Mohammad Mohammadi

Communications in Statistics - Theory and Methods, 2020, vol. 49, issue 11, 2728-2748

Abstract: This paper proposes a new mathematical model for the reliability-redundancy allocation problem (RRAP) with a choice of redundancy strategies. To maximize the reliability of a system, this model chooses the best redundancy strategy from among both active and standby ones for each subsystem. For those with a standby strategy, a continuous time Markov chain model is used to calculate the exact reliability values. In order to solve the proposed mixed-integer non-linear programing model, a powerful evolutionary algorithm, called water cycle algorithm (WCA), is developed and implemented on three famous benchmark problems. Finally, the results of different benchmark problems are compared with those previously reported to show the superiority of the proposed model and the efficiency of WCA.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2019.1580741 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:49:y:2020:i:11:p:2728-2748

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2019.1580741

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:lstaxx:v:49:y:2020:i:11:p:2728-2748