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Modified cuckoo search: A new gradient free optimisation algorithm

Author

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  • Walton, S.
  • Hassan, O.
  • Morgan, K.
  • Brown, M.R.

Abstract

A new robust optimisation algorithm, which can be regarded as a modification of the recently developed cuckoo search, is presented. The modification involves the addition of information exchange between the top eggs, or the best solutions. Standard optimisation benchmarking functions are used to test the effects of these modifications and it is demonstrated that, in most cases, the modified cuckoo search performs as well as, or better than, the standard cuckoo search, a particle swarm optimiser, and a differential evolution strategy. In particular the modified cuckoo search shows a high convergence rate to the true global minimum even at high numbers of dimensions.

Suggested Citation

  • Walton, S. & Hassan, O. & Morgan, K. & Brown, M.R., 2011. "Modified cuckoo search: A new gradient free optimisation algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 44(9), pages 710-718.
    • Handle: RePEc:eee:chsofr:v:44:y:2011:i:9:p:710-718
    DOI: 10.1016/j.chaos.2011.06.004
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    Cited by:

    1. Piechocki, Janusz & Ambroziak, Dominik & Palkowski, Aleksander & Redlarski, Grzegorz, 2014. "Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms," Applied Energy, Elsevier, vol. 114(C), pages 901-908.
    2. Thang Trung Nguyen & Bach Hoang Dinh & Nguyen Vu Quynh & Minh Quan Duong & Le Van Dai, 2018. "A Novel Algorithm for Optimal Operation of Hydrothermal Power Systems under Considering the Constraints in Transmission Networks," Energies, MDPI, vol. 11(1), pages 1-21, January.
    3. Shouheng Tuo & Junying Zhang & Xiguo Yuan & Yuanyuan Zhang & Zhaowen Liu, 2016. "FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-27, March.
    4. Xie, Bing & Ge, Fudong, 2023. "Parameters and order identification of fractional-order epidemiological systems by Lévy-PSO and its application for the spread of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    5. Oruc, Ridvan & Baklacioglu, Tolga, 2022. "Modeling of aircraft performance parameters with metaheuristic methods to achieve specific excess power contours using energy maneuverability method," Energy, Elsevier, vol. 259(C).
    6. Jiang, Ping & Liu, Feng & Song, Yiliao, 2017. "A hybrid forecasting model based on date-framework strategy and improved feature selection technology for short-term load forecasting," Energy, Elsevier, vol. 119(C), pages 694-709.
    7. Li Xiangfei & Zhang Zaisheng & Huang Chao, 2014. "An EPC Forecasting Method for Stock Index Based on Integrating Empirical Mode Decomposition, SVM and Cuckoo Search Algorithm," Journal of Systems Science and Information, De Gruyter, vol. 2(6), pages 481-504, December.
    8. Jeng-Shyang Pan & Pei-Cheng Song & Shu-Chuan Chu & Yan-Jun Peng, 2020. "Improved Compact Cuckoo Search Algorithm Applied to Location of Drone Logistics Hub," Mathematics, MDPI, vol. 8(3), pages 1-19, March.
    9. Yang, Qiangda & Liu, Peng & Zhang, Jie & Dong, Ning, 2022. "Combined heat and power economic dispatch using an adaptive cuckoo search with differential evolution mutation," Applied Energy, Elsevier, vol. 307(C).
    10. Coelho, Leandro dos Santos & Klein, Carlos Eduardo & Sabat, Samrat L. & Mariani, Viviana Cocco, 2014. "Optimal chiller loading for energy conservation using a new differential cuckoo search approach," Energy, Elsevier, vol. 75(C), pages 237-243.
    11. Weibo Zhao & Dongxiao Niu, 2017. "Prediction of CO 2 Emission in China’s Power Generation Industry with Gauss Optimized Cuckoo Search Algorithm and Wavelet Neural Network Based on STIRPAT model with Ridge Regression," Sustainability, MDPI, vol. 9(12), pages 1-15, December.

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