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Multi-Population Genetic Algorithm Based on Adaptive Learning Mechanism

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Advancements in Mechatronics and Intelligent Robotics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1220))

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Abstract

Traditional genetic algorithm has some disadvantages, such as slow convergence, unstable, and easy to fall into local extreme. In order to overcome these disadvantages, an improved genetic algorithm is proposed in the present study. First, based on the analysis of advantages and disadvantages of learning mechanisms in literature, new improvements of learning mechanisms under the multi-population parallel GA are made. In previous studies, gene patterns from which other individuals can learn will be extracted from the excellent individuals of the population, this study improved the learning mechanism by adaptively changing the related control parameters, and dynamically controlling the process of the learning mechanism. Simulation results show that the new algorithm has a great improvement in many aspects of the global optimization, such as convergence speed, the accuracy of the solution, and stability.

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Author information

Authors and Affiliations

  1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, Yunnan, China

    Jiawen Pan, Qian Qian, Yong Feng & Yunfa Fu

  2. Yunnan Key Laboratory of Computer Technology Applications, Kunming University of Science and Technology, Kunming, 650500, Yunnan, China

    Jiawen Pan, Qian Qian & Yong Feng

Authors
  1. Jiawen Pan
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  2. Qian Qian
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  3. Yong Feng
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  4. Yunfa Fu
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Corresponding author

Correspondence to Qian Qian .

Editor information

Editors and Affiliations

  1. School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China

    Zhengtao Yu

  2. Department of Computer Science and Engineering, SOA University, Bhubaneswar, India

    Srikanta Patnaik

  3. Department of Information Management and Business Analytics, Montclair State University, Montclair, NJ, USA

    John Wang

  4. Department of Computer Science and Engineering, JIS University, Kolkata, India

    Nilanjan Dey

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© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Pan, J., Qian, Q., Feng, Y., Fu, Y. (2021). Multi-Population Genetic Algorithm Based on Adaptive Learning Mechanism. In: Yu, Z., Patnaik, S., Wang, J., Dey, N. (eds) Advancements in Mechatronics and Intelligent Robotics. Advances in Intelligent Systems and Computing, vol 1220. Springer, Singapore. https://doi.org/10.1007/978-981-16-1843-7_38

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