Models for inverse minimum spanning tree problem with fuzzy edge weights

Jingyu Zhang, Jian Zhou, Shuya Zhong

Research output: Contribution to journalArticlepeer-review

5 Citations (SciVal)


An inverse minimum spanning tree problem is to make the least modification on the edge weights such that a predetermined spanning tree is a minimum spanning tree with respect to the new edge weights. In this paper, a type of fuzzy inverse minimum spanning tree problem is introduced from a LAN reconstruction problem, where the weights of edges are assumed to be fuzzy variables. The concept of fuzzy α-minimum spanning tree is initialized, and subsequently a fuzzy α-minimum spanning tree model and a credibility maximization model are presented to formulate the problem according to different decision criteria. In order to solve the two fuzzy models, a fuzzy simulation for computing credibility is designed and then embedded into a genetic algorithm to produce some hybrid intelligent algorithms. Finally, some computational examples are given to illustrate the effectiveness of the proposed algorithms.

Original languageEnglish
Pages (from-to)2691-2702
Number of pages12
JournalJournal of Intelligent and Fuzzy Systems
Issue number5
Publication statusPublished - 31 Dec 2014

Bibliographical note

Publisher Copyright:
© 2014 - IOS Press and the authors.


  • fuzzy programming
  • genetic algorithm
  • inverse optimization
  • Minimum spanning tree

ASJC Scopus subject areas

  • Statistics and Probability
  • General Engineering
  • Artificial Intelligence


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