Title
A tabu search algorithm for the minmax regret minimum spanning tree problem with interval data
Abstract
This paper deals with the strongly NP-hard minmax regret version of the minimum spanning tree problem with interval costs. The best known exact algorithms solve the problem in reasonable time for rather small graphs. In this paper an algorithm based on the idea of tabu search is constructed. Some properties of the local minima are shown. Exhaustive computational tests for various classes of graphs are performed. The obtained results suggest that the proposed tabu search algorithm quickly outputs optimal solutions for the smaller instances, previously discussed in the existing literature. Furthermore, some arguments that this algorithm performs well also for larger instances are provided.
Year
DOI
Venue
2012
10.1007/s10732-012-9200-z
J. Heuristics
Keywords
Field
DocType
Spanning tree,Minmax regret,Interval data,Tabu search
Minimax,Guided Local Search,Artificial intelligence,Spanning tree,Minimum spanning tree,Mathematical optimization,Regret,Algorithm,Maxima and minima,Interval data,Machine learning,Tabu search,Mathematics
Journal
Volume
Issue
ISSN
18
4
1381-1231
Citations 
PageRank 
References 
9
0.58
17
Authors
3
Name
Order
Citations
PageRank
Adam Kasperski135233.64
Mariusz Makuchowski2221.30
Paweł Zieliński327419.73