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An Improved Binary Wolf Pack Algorithm Based on Adaptive Step Length and Improved Update Strategy for 0-1 Knapsack Problems

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Data Science (ICPCSEE 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 728))

Abstract

Binary wolf pack algorithm (BWPA) is a kind of intelligence algorithm which can solve combination optimization problems in discrete spaces. Based on BWPA, an improved binary wolf pack algorithm (AIBWPA) can be proposed by adopting adaptive step length and improved update strategy of wolf pack. AIBWPA is applied to 10 classic 0-1 knapsack problems and compared with BWPA, DPSO, which proves that AIBWPA has higher optimization accuracy and better computational robustness. AIBWPA makes the parameters simple, protects the population diversity and enhances the global convergence.

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Author information

Authors and Affiliations

  1. School of Mathematics and Statistics, Xidian University, Xi’an, 710126, Shaanxi, China

    Liting Guo & Sanyang Liu

Authors
  1. Liting Guo
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  2. Sanyang Liu
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Corresponding author

Correspondence to Liting Guo .

Editor information

Editors and Affiliations

  1. Central South University, Changsha, China

    Beiji Zou

  2. Harbin Engineering University, Harbin, China

    Qilong Han

  3. Harbin University of Science and Technology, Harbin, China

    Guanglu Sun

  4. Northeast Forestry University, Harbin, China

    Weipeng Jing

  5. Huaihua University, Huaihua, Hunan, China

    Xiaoning Peng

  6. Sciences of Country Tripod Institute of Data Science, Harbin, China

    Zeguang Lu

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© 2017 Springer Nature Singapore Pte Ltd.

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Guo, L., Liu, S. (2017). An Improved Binary Wolf Pack Algorithm Based on Adaptive Step Length and Improved Update Strategy for 0-1 Knapsack Problems. In: Zou, B., Han, Q., Sun, G., Jing, W., Peng, X., Lu, Z. (eds) Data Science. ICPCSEE 2017. Communications in Computer and Information Science, vol 728. Springer, Singapore. https://doi.org/10.1007/978-981-10-6388-6_37

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  • DOI: https://doi.org/10.1007/978-981-10-6388-6_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6387-9

  • Online ISBN: 978-981-10-6388-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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