On bicriterion minimal spanning trees: an approximation
Computers and Operations Research
On the approximability of some maximum spanning tree problems
Theoretical Computer Science - Special issue: Latin American theoretical informatics
The minimum labeling spanning trees
Information Processing Letters
An effective genetic algorithm approach to the quadratic minimum spanning tree problem
Computers and Operations Research
On the minimum label spanning tree problem
Information Processing Letters
A note on chance constrained programming with fuzzy coefficients
Fuzzy Sets and Systems
A shortest path problem on a network with fuzzy arc lengths
Fuzzy Sets and Systems
A faster algorithm for the inverse spanning tree problem
Journal of Algorithms
Approximation algorithms for some optimum communication spanning tree problems
Discrete Applied Mathematics
A fuzzy max-flow min-cut theorem
Fuzzy Sets and Systems
Spanning trees with constraints on the leaf degree
Discrete Applied Mathematics - Special issue on selected papers from First Japanese-Hungarian Symposium for Discrete Mathematics and its Applications
Theory and Practice of Uncertain Programming
Theory and Practice of Uncertain Programming
An exact algorithm for the maximum leaf spanning tree problem
Computers and Operations Research
Generalized path-finding algorithms on semirings and the fuzzy shortest path problem
Journal of Computational and Applied Mathematics - Special issue: Proceedings of the international conference on linear algebra and arithmetic, Rabat, Morocco, 28-31 May 2001
Minimum restricted diameter spanning trees
Discrete Applied Mathematics
Graph Theory With Applications
Graph Theory With Applications
On the History of the Minimum Spanning Tree Problem
IEEE Annals of the History of Computing
On the minimum diameter spanning tree problem
Information Processing Letters
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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.