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Chaotic annealing with hypothesis test for function optimization in noisy environments

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  • Pan, Hui
  • Wang, Ling
  • Liu, Bo

Abstract

As a special mechanism to avoid being trapped in local minimum, the ergodicity property of chaos has been used as a novel searching technique for optimization problems, but there is no research work on chaos for optimization in noisy environments. In this paper, the performance of chaotic annealing (CA) for uncertain function optimization is investigated, and a new hybrid approach (namely CAHT) that combines CA and hypothesis test (HT) is proposed. In CAHT, the merits of CA are applied for well exploration and exploitation in searching space, and solution quality can be identified reliably by hypothesis test to reduce the repeated search to some extent and to reasonably estimate performance for solution. Simulation results and comparisons show that, chaos is helpful to improve the performance of SA for uncertain function optimization, and CAHT can further improve the searching efficiency, quality and robustness.

Suggested Citation

  • Pan, Hui & Wang, Ling & Liu, Bo, 2008. "Chaotic annealing with hypothesis test for function optimization in noisy environments," Chaos, Solitons & Fractals, Elsevier, vol. 35(5), pages 888-894.
    • Handle: RePEc:eee:chsofr:v:35:y:2008:i:5:p:888-894
    DOI: 10.1016/j.chaos.2006.05.070
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    References listed on IDEAS

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    1. Liu, Bo & Wang, Ling & Jin, Yi-Hui & Tang, Fang & Huang, De-Xian, 2005. "Improved particle swarm optimization combined with chaos," Chaos, Solitons & Fractals, Elsevier, vol. 25(5), pages 1261-1271.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Hong, Wei-Chiang, 2011. "Electric load forecasting by seasonal recurrent SVR (support vector regression) with chaotic artificial bee colony algorithm," Energy, Elsevier, vol. 36(9), pages 5568-5578.

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