• DocumentCode
    1612549
  • Title

    The robust redundancy allocation problem of series-parallel systems

  • Author

    Wei Wang ; Junlin Xiong ; Min Xie

  • Author_Institution
    Dept. of Autom., Univ. of Sci. & Technol. of China, Hefei, China
  • fYear
    2013
  • Firstpage
    222
  • Lastpage
    227
  • Abstract
    Redundancy allocation is a technique that has been widely used to improve systems reliability. In this paper, the interval analysis is introduced to represent imprecise component reliabilities, and an order relation is applied in the comparison of interval values. We propose a mathematical model to deal with constrained redundancy optimization of series-parallel systems with interval-valued component reliabilities. The objective function is extended to an interval-valued function in the proposed model, and a dynamic penalty genetic algorithm (GA) is developed to search the best solution and the optimum system reliability. Several numerical examples are given to illustrate the proposed method, and the experimental results have shown that the interval mathematics is an efficient tool to solve the redundancy allocation problem (RAP) of systems with interval-valued component reliabilities.
  • Keywords
    dynamic programming; genetic algorithms; redundancy; reliability theory; GA; RAP; constrained redundancy optimization; dynamic penalty genetic algorithm; interval analysis; interval mathematics; interval-valued component reliabilities; mathematical model; optimum system reliability; order relation; robust redundancy allocation problem; series-parallel systems; Linear programming; Mathematical model; Redundancy; Reliability engineering; Resource management; Robustness; genetic algorithm; interval analysis; redundancy allocation; system reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Chinese Automation Congress (CAC), 2013
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-0332-0
  • Type

    conf

  • DOI
    10.1109/CAC.2013.6775732
  • Filename
    6775732