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The Fuzzy Weighted k-Cardinality Tree and Its Hybrid Genetic Algorithm

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Fuzzy Systems and Knowledge Discovery (FSKD 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4223))

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Abstract

The k-tree problem is to find a tree with k vertices in a given graph such that the total cost is minimum and is known to be NP-hard. In this paper, the k-tree problem with fuzzy weights is firstly formulated as the chance-constrained programming by using the possibility measure and the credibility measure. Then an oriented tree and knowledge-based hybrid genetic algorithm is designed for solving the proposed fuzzy programming models.

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Author information

Authors and Affiliations

  1. School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, 730070, China

    Linzhong Liu, Ruichun He & Yinzhen Li

  2. Dept. of Mathematical Sciences, Tsinghua University, Beijing, 100084, China

    Linzhong Liu

Authors
  1. Linzhong Liu
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  2. Ruichun He
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  3. Yinzhen Li
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Editor information

Editors and Affiliations

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

    Lipo Wang

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

    Licheng Jiao

  3. School of Electrical and Electronic Engineering, Xidian University, 710071, Xi’an, China

    Guanming Shi

  4. School of Information Technology and Electrical Engineering, The University of Queensland, 4072, Brisbane, Queensland, Australia

    Xue Li

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

    Jing Liu

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© 2006 Springer-Verlag Berlin Heidelberg

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Liu, L., He, R., Li, Y. (2006). The Fuzzy Weighted k-Cardinality Tree and Its Hybrid Genetic Algorithm. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_127

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  • DOI: https://doi.org/10.1007/11881599_127

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45916-3

  • Online ISBN: 978-3-540-45917-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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