IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v41y2009i2p594-602.html
   My bibliography  Save this article

Reliability–redundancy optimization by means of a chaotic differential evolution approach

Author

Listed:
  • Coelho, Leandro dos Santos

Abstract

The reliability design is related to the performance analysis of many engineering systems. The reliability–redundancy optimization problems involve selection of components with multiple choices and redundancy levels that produce maximum benefits, can be subject to the cost, weight, and volume constraints. Classical mathematical methods have failed in handling nonconvexities and nonsmoothness in optimization problems. As an alternative to the classical optimization approaches, the meta-heuristics have been given much attention by many researchers due to their ability to find an almost global optimal solution in reliability–redundancy optimization problems. Evolutionary algorithms (EAs) – paradigms of evolutionary computation field – are stochastic and robust meta-heuristics useful to solve reliability–redundancy optimization problems. EAs such as genetic algorithm, evolutionary programming, evolution strategies and differential evolution are being used to find global or near global optimal solution. A differential evolution approach based on chaotic sequences using Lozi’s map for reliability–redundancy optimization problems is proposed in this paper. The proposed method has a fast convergence rate but also maintains the diversity of the population so as to escape from local optima. An application example in reliability–redundancy optimization based on the overspeed protection system of a gas turbine is given to show its usefulness and efficiency. Simulation results show that the application of deterministic chaotic sequences instead of random sequences is a possible strategy to improve the performance of differential evolution.

Suggested Citation

  • Coelho, Leandro dos Santos, 2009. "Reliability–redundancy optimization by means of a chaotic differential evolution approach," Chaos, Solitons & Fractals, Elsevier, vol. 41(2), pages 594-602.
    • Handle: RePEc:eee:chsofr:v:41:y:2009:i:2:p:594-602
    DOI: 10.1016/j.chaos.2008.02.028
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077908000891
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2008.02.028?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zuo, X.Q. & Fan, Y.S., 2006. "A chaos search immune algorithm with its application to neuro-fuzzy controller design," Chaos, Solitons & Fractals, Elsevier, vol. 30(1), pages 94-109.
    2. Li, Lixiang & Yang, Yixian & Peng, Haipeng & Wang, Xiangdong, 2006. "Parameters identification of chaotic systems via chaotic ant swarm," Chaos, Solitons & Fractals, Elsevier, vol. 28(5), pages 1204-1211.
    3. Yang, Dixiong & Li, Gang & Cheng, Gengdong, 2007. "On the efficiency of chaos optimization algorithms for global optimization," Chaos, Solitons & Fractals, Elsevier, vol. 34(4), pages 1366-1375.
    4. Liu, Bo & Wang, Ling & Jin, Yi-Hui & Huang, De-Xian & Tang, Fang, 2007. "Control and synchronization of chaotic systems by differential evolution algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 412-419.
    5. Gen, Mitsuo & Yun, YoungSu, 2006. "Soft computing approach for reliability optimization: State-of-the-art survey," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1008-1026.
    6. Chang, Wei-Der, 2007. "Parameter identification of Chen and Lü systems: A differential evolution approach," Chaos, Solitons & Fractals, Elsevier, vol. 32(4), pages 1469-1476.
    7. Ali, M.M., 2007. "Differential evolution with preferential crossover," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1137-1147, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. dos Santos Coelho, Leandro, 2009. "Tuning of PID controller for an automatic regulator voltage system using chaotic optimization approach," Chaos, Solitons & Fractals, Elsevier, vol. 39(4), pages 1504-1514.
    2. Wei-Chiang Hong & Yucheng Dong & Chien-Yuan Lai & Li-Yueh Chen & Shih-Yung Wei, 2011. "SVR with Hybrid Chaotic Immune Algorithm for Seasonal Load Demand Forecasting," Energies, MDPI, vol. 4(6), pages 1-18, June.
    3. Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2009. "Chaotic artificial immune approach applied to economic dispatch of electric energy using thermal units," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2376-2383.
    4. Tang, Yinggan & Guan, Xinping, 2009. "Parameter estimation for time-delay chaotic system by particle swarm optimization," Chaos, Solitons & Fractals, Elsevier, vol. 40(3), pages 1391-1398.
    5. Qasim M. Zainel & Saad M. Darwish & Murad B. Khorsheed, 2022. "Employing Quantum Fruit Fly Optimization Algorithm for Solving Three-Dimensional Chaotic Equations," Mathematics, MDPI, vol. 10(21), pages 1-21, November.
    6. Tang, Yinggan & Cui, Mingyong & Li, Lixiang & Peng, Haipeng & Guan, Xinping, 2009. "Parameter identification of time-delay chaotic system using chaotic ant swarm," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 2097-2102.
    7. Tang, Yinggan & Guan, Xinping, 2009. "Parameter estimation of chaotic system with time-delay: A differential evolution approach," Chaos, Solitons & Fractals, Elsevier, vol. 42(5), pages 3132-3139.
    8. Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2009. "A novel chaotic particle swarm optimization approach using Hénon map and implicit filtering local search for economic load dispatch," Chaos, Solitons & Fractals, Elsevier, vol. 39(2), pages 510-518.
    9. Coelho, Leandro dos Santos, 2009. "An efficient particle swarm approach for mixed-integer programming in reliability–redundancy optimization applications," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 830-837.
    10. Li, Chaoshun & Zhou, Jianzhong & Xiao, Jian & Xiao, Han, 2012. "Parameters identification of chaotic system by chaotic gravitational search algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 45(4), pages 539-547.
    11. Sun, Yeong-Jeu, 2009. "An exponential observer for the generalized Rossler chaotic system," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2457-2461.
    12. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2013. "Cold-standby sequencing optimization considering mission cost," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 28-34.
    13. Salil Bharany & Sandeep Sharma & Surbhi Bhatia & Mohammad Khalid Imam Rahmani & Mohammed Shuaib & Saima Anwar Lashari, 2022. "Energy Efficient Clustering Protocol for FANETS Using Moth Flame Optimization," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    14. Sultan Almotairi & Elsayed Badr & Mustafa Abdul Salam & Alshimaa Dawood, 2023. "Three Chaotic Strategies for Enhancing the Self-Adaptive Harris Hawk Optimization Algorithm for Global Optimization," Mathematics, MDPI, vol. 11(19), pages 1-27, October.
    15. Levitin, Gregory & Xing, Liudong & Haim, Hanoch Ben & Dai, Yuanshun, 2019. "Optimal structure of series system with 1-out-of-n warm standby subsystems performing operation and rescue functions," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 523-531.
    16. Shang, Li-Jen & Shyu, Kuo-Kai, 2009. "A method for extracting chaotic signal from noisy environment," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 1120-1125.
    17. Safari, Jalal, 2012. "Multi-objective reliability optimization of series-parallel systems with a choice of redundancy strategies," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 10-20.
    18. Cheng, Shen & Zhao, Gaiju & Gao, Ming & Shi, Yuetao & Huang, Mingming & Yousefi, Nasser, 2021. "Optimal hybrid energy system for locomotive utilizing improved Locust Swarm optimizer," Energy, Elsevier, vol. 218(C).
    19. MacKenzie, Cameron A. & Hu, Chao, 2019. "Decision making under uncertainty for design of resilient engineered systems," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    20. Li, Yuying & Wen, Qiaoyan & Li, Lixiang & Peng, Haipeng, 2009. "Hybrid chaotic ant swarm optimization," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 880-889.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:41:y:2009:i:2:p:594-602. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.