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Reliability optimization using multiobjective ant colony system approaches

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  • Zhao, Jian-Hua
  • Liu, Zhaoheng
  • Dao, My-Thien

Abstract

The multiobjective ant colony system (ACS) meta-heuristic has been developed to provide solutions for the reliability optimization problem of series-parallel systems. This type of problems involves selection of components with multiple choices and redundancy levels that produce maximum benefits, and is subject to the cost and weight constraints at the system level. These are very common and realistic problems encountered in conceptual design of many engineering systems. It is becoming increasingly important to develop efficient solutions to these problems because many mechanical and electrical systems are becoming more complex, even as development schedules get shorter and reliability requirements become very stringent. The multiobjective ACS algorithm offers distinct advantages to these problems compared with alternative optimization methods, and can be applied to a more diverse problem domain with respect to the type or size of the problems. Through the combination of probabilistic search, multiobjective formulation of local moves and the dynamic penalty method, the multiobjective ACSRAP, allows us to obtain an optimal design solution very frequently and more quickly than with some other heuristic approaches. The proposed algorithm was successfully applied to an engineering design problem of gearbox with multiple stages.

Suggested Citation

  • Zhao, Jian-Hua & Liu, Zhaoheng & Dao, My-Thien, 2007. "Reliability optimization using multiobjective ant colony system approaches," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 109-120.
    • Handle: RePEc:eee:reensy:v:92:y:2007:i:1:p:109-120
    DOI: 10.1016/j.ress.2005.12.001
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    References listed on IDEAS

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    1. David W. Coit & Alice E. Smith & David M. Tate, 1996. "Adaptive Penalty Methods for Genetic Optimization of Constrained Combinatorial Problems," INFORMS Journal on Computing, INFORMS, vol. 8(2), pages 173-182, May.
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    1. Ramezani, Reza & Ghavidel, Abolfazl & Sedaghat, Yasser, 2021. "Exact and efficient reliability and performance optimization of synchronous task graphs," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    2. Meisam Sadeghi & Emad Roghanian & Hamid Shahriari & Hassan Sadeghi, 2021. "Reliability optimization for non-repairable series-parallel systems with a choice of redundancy strategies and heterogeneous components: Erlang time-to-failure distribution," Journal of Risk and Reliability, , vol. 235(3), pages 509-528, June.
    3. Liu, Yu & Chen, Yiming & Jiang, Tao, 2018. "On sequence planning for selective maintenance of multi-state systems under stochastic maintenance durations," European Journal of Operational Research, Elsevier, vol. 268(1), pages 113-127.
    4. Lust, T. & Roux, O. & Riane, F., 2009. "Exact and heuristic methods for the selective maintenance problem," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1166-1177, September.
    5. Abdullah Konak & Alice E. Smith, 2011. "Efficient Optimization of Reliable Two-Node Connected Networks: A Biobjective Approach," INFORMS Journal on Computing, INFORMS, vol. 23(3), pages 430-445, August.
    6. Khalili-Damghani, Kaveh & Amiri, Maghsoud, 2012. "Solving binary-state multi-objective reliability redundancy allocation series-parallel problem using efficient epsilon-constraint, multi-start partial bound enumeration algorithm, and DEA," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 35-44.
    7. Ali Salmasnia & Sadegh Noori & Hadi Mokhtari, 2019. "A redundancy allocation problem by using utility function method and ant colony optimization: tradeoff between availability and total cost," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(3), pages 416-428, June.
    8. Khalili-Damghani, Kaveh & Abtahi, Amir-Reza & Tavana, Madjid, 2013. "A new multi-objective particle swarm optimization method for solving reliability redundancy allocation problems," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 58-75.
    9. Andrés Cacereño & David Greiner & Blas J. Galván, 2021. "Multi-Objective Optimum Design and Maintenance of Safety Systems: An In-Depth Comparison Study Including Encoding and Scheduling Aspects with NSGA-II," Mathematics, MDPI, vol. 9(15), pages 1-39, July.
    10. Zhang, Enze & Wu, Yifei & Chen, Qingwei, 2014. "A practical approach for solving multi-objective reliability redundancy allocation problems using extended bare-bones particle swarm optimization," Reliability Engineering and System Safety, Elsevier, vol. 127(C), pages 65-76.

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