EconPapers    
Economics at your fingertips  
 

Profit optimisation of the multiple-vacation machine repair problem using particle swarm optimisation

Kuo-Hsiung Wang, Cheng-Dar Liou and Ya-Lin Wang

International Journal of Systems Science, 2014, vol. 45, issue 8, 1769-1780

Abstract: This paper investigates a multiple-vacation M/M/1 warm-standby machine repair problem with an unreliable repairman. We first apply a matrix-analytic method to obtain the steady-state probabilities. Next, we construct the total expected profit per unit time and formulate an optimisation problem to find the maximum profit. The particle swarm optimisation (PSO) algorithm is implemented to determine the optimal number of warm standbys S* and the service rate μ* as well as vacation rate ν* simultaneously at the optimal maximum profit. We compare the searching results of the PSO algorithm with those of exhaustive search method to ensure the searching quality of the PSO algorithm. Sensitivity analysis with numerical illustrations is also provided.

Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2012.757378 (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:tsysxx:v:45:y:2014:i:8:p:1769-1780

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2012.757378

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tsysxx:v:45:y:2014:i:8:p:1769-1780