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Multi-objective genetic algorithm for solving N-version program design problem

Author

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  • Yamachi, Hidemi
  • Tsujimura, Yasuhiro
  • Kambayashi, Yasushi
  • Yamamoto, Hisashi

Abstract

N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently.

Suggested Citation

  • Yamachi, Hidemi & Tsujimura, Yasuhiro & Kambayashi, Yasushi & Yamamoto, Hisashi, 2006. "Multi-objective genetic algorithm for solving N-version program design problem," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1083-1094.
    • Handle: RePEc:eee:reensy:v:91:y:2006:i:9:p:1083-1094
    DOI: 10.1016/j.ress.2005.11.045
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    References listed on IDEAS

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    1. Gregory Levitin, 2005. "Optimal Version Sequencing In Fault-Tolerant Programs," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-18.
    2. James C. Bean, 1994. "Genetic Algorithms and Random Keys for Sequencing and Optimization," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 154-160, May.
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    Cited by:

    1. Min Xie & Chengjie Xiong & Szu-Hui Ng, 2014. "A study of N-version programming and its impact on software availability," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(10), pages 2145-2157, October.
    2. Zhao, Jiangbin & Si, Shubin & Cai, Zhiqiang, 2019. "A multi-objective reliability optimization for reconfigurable systems considering components degradation," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 104-115.

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