The fuzzy weighted k-cardinality tree and its hybrid genetic algorithm

  • Authors:
  • Linzhong Liu;Ruichun He;Yinzhen Li

  • Affiliations:
  • School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, China;School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, China;School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, China

  • Venue:
  • FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
  • Year:
  • 2006

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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.