A note on a reliability redundancy allocation problem using a tuned parameter genetic algorithm

Amirhossain Chambari (), Javad Sadeghi (), Fakhri Bakhtiari () and Reza Jahangard ()
Additional contact information
Amirhossain Chambari: Islamic Azad University
Javad Sadeghi: State University of New York at Binghamton
Fakhri Bakhtiari: Payame Noor University
Reza Jahangard: Islamic Azad University

OPSEARCH, 2016, vol. 53, issue 2, No 13, 426-442

Abstract: Abstract This paper presents an improved continuous genetic algorithm (CGA) to optimize the reliability redundancy allocation problem (RRAP) which determines the best redundancy strategies, the number of components, and levels of each subsystem to maximize the system reliability. In this system, both active and cold-standby redundancies can be chosen for individual subsystems. The RRAP belongs to NP-hard problems in the computational complexity theory that is the main reason for employing CGA to solve it. In addition, the response surface methodology (RSM) is used to increase the performance of CGA considering the design of experiments. This algorithm employs a new chromosome so that frees offspring to repair during the evolution process. Considering several numerical examples, the proposed algorithm presents better solutions than the previous studies based on the system reliability. Finally, the conclusion and future research are considered.

Keywords: Redundancy allocation problem; Series–parallel systems; Continuous genetic algorithm; Parameter tuning; Response surface methodology (RSM) (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s12597-015-0230-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:opsear:v:53:y:2016:i:2:d:10.1007_s12597-015-0230-9

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/12597

DOI: 10.1007/s12597-015-0230-9

Access Statistics for this article

OPSEARCH is currently edited by Birendra Mandal

More articles in OPSEARCH from Springer, Operational Research Society of India
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().