This paper gives an algorithm for finding the minimum weight tree having k edges in an edge weighted graph. The algorithm combines a search and optimization technique based on pheromone with a weight based greedy local optimization. Experimental results on a large set of problem instances show that this algorithm matches or surpasses other algorithms including an ant colony optimization algorithm, a tabu search algorithm, an evolutionary algorithm and a greedy-based algorithm on all but one of the 138 tested instances.
|Original language||English (US)|
|Number of pages||12|
|Journal||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Publication status||Published - Dec 1 2004|
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)