Abstract
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 language | English |
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Pages (from-to) | 2691-2702 |
Number of pages | 12 |
Journal | Journal of Intelligent and Fuzzy Systems |
Volume | 27 |
Issue number | 5 |
DOIs | |
Publication status | Published - 31 Dec 2014 |
Bibliographical note
Publisher Copyright:© 2014 - IOS Press and the authors.
Keywords
- fuzzy programming
- genetic algorithm
- inverse optimization
- Minimum spanning tree
ASJC Scopus subject areas
- Statistics and Probability
- General Engineering
- Artificial Intelligence