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Recent Advances in Evolutionary Programming

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Book cover Bio-inspired Computing – Theories and Applications (BIC-TA 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 682))

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Abstract

In this paper, we provide an overview of some recent advances in evolutionary programming. We mainly discuss the principle and technical method of design for classical evolutionary programming and improving evolutionary programming (IEP). IEP has included many types of improving methods to solve realistic problems: fast evolutionary programming, self-adaptive Cauchy evolutionary programming, mixed mutation strategy in evolutionary programming, parallel evolutionary programming, Quality of Transmission (QoT) aware evolutionary programming algorithm, shifting classical evolutionary programming, and surrogate-assisted evolutionary programming. The above methods and some issues related to the future development of evolutionary programming are discussed in this paper.

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Acknowledgment

This research is supported by the National Natural Science Foundation of China (No. 71331008), the Program for New Century Excellent Talents in University, Foundation for the Author of National Excellent Doctoral Dissertation of PR China (2014-92), the Youth Training Program for Innovation and Entrepreneurship Platform of Science and Technology at Hunan Province, the Outstanding Youth Fund Project of Hunan Provincial Natural Science Foundation (S2015J5050), the Top-notch Innovative Talents Training Plan of National University of Defense Technology, the Outstanding Youth Fund Project of National University of Defense Technology (JQ14-05-01), the Fundamental Research Funds for the Central Universities (531107050772) and Shenzhen Basic Research Project for Development of Science and Technology (JCYJ20160530141956915).

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Authors and Affiliations

  1. School of Information Systems and Management, National University of Defense Technology, Changsha, 410073, Hunan, China

    Jing Yu & Lining Xing

Authors
  1. Jing Yu
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  2. Lining Xing
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Corresponding author

Correspondence to Lining Xing .

Editor information

Editors and Affiliations

  1. Xidian University , Xi’an, China

    Maoguo Gong

  2. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  3. China University of Petroleum, Qingdao, China

    Tao Song

  4. Southwest Jiaotong University , Chengdu, China

    Gexiang Zhang

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Yu, J., Xing, L. (2016). Recent Advances in Evolutionary Programming. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 682. Springer, Singapore. https://doi.org/10.1007/978-981-10-3614-9_25

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  • DOI: https://doi.org/10.1007/978-981-10-3614-9_25

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3613-2

  • Online ISBN: 978-981-10-3614-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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