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A New Macroevolutionary Algorithm for Constrained Optimization Problems

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Advances in Natural Computation (ICNC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4221))

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Abstract

Macroevolutionary algorithm (MA) is a new approach to optimization problems based on extinction patterns in macroevolution. It is different from the traditional population-level evolutionary algorithms such as genetic algorithms. In this paper, a new macroevolutionary algorithm based on uniform design is presented for solving nonlinear constrained optimization problems. Constraints are handled by embodying them in an augmented Lagrangian function, where the penalty parameters and multipliers are adapted as the execution of the algorithm proceeds. The efficiency of the proposed methodology is illustrated by solving numerous constrained optimization problems that can be found in the literature.

Supported by SRF for ROCS, SEM; Taishan Scholarship program of Shandong Province.

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Author information

Authors and Affiliations

  1. School of Automation Engineering, Qingdao University, Qingdao, 266071, China

    Jihui Zhang

  2. School of Mathematics Sciences, Qingdao University, Qingdao, 266071, China

    Junqin Xu

Authors
  1. Jihui Zhang
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  2. Junqin Xu
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Editor information

Editors and Affiliations

  1. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  3. School of Electronic Engineering, Xidian Univ., 710071, Xi’an, P.R. China

    Xin-bo Gao

  4. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

  5. Multi-Agent Systems Lab,Department of Computer Science, University of Science and Technology of China, 230026, Hefei, China

    Feng Wu

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© 2006 Springer-Verlag Berlin Heidelberg

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Zhang, J., Xu, J. (2006). A New Macroevolutionary Algorithm for Constrained Optimization Problems. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_110

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  • DOI: https://doi.org/10.1007/11881070_110

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45901-9

  • Online ISBN: 978-3-540-45902-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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