Article

NEW METAHEURISTIC APPROACHES FOR THE LEAF-CONSTRAINED MINIMUM SPANNING TREE PROBLEM

Asia-Pacific Journal of Operational Research (APJOR) 01/2008; 25(04):575-589. pp.575-589
Source: RePEc

ABSTRACT Given an undirected, connected, weighted graph, the leaf-constrained minimum spanning tree (LCMST) problem seeks a spanning tree of the graph with smallest weight among all spanning trees of the graph, which contains at least l leaves. In this paper we have proposed two new metaheuristic approaches for the LCMST problem. One is an ant-colony optimization (ACO) algorithm, whereas the other is a tabu search based algorithm. Similar to a previously proposed genetic algorithm, these metaheuristic approaches also use the subset coding that represents a leaf-constrained spanning tree by the set of its interior vertices. Our new approaches perform well in comparison with two best heuristics reported in the literature for the problem — the subset-coded genetic algorithm and a greedy heuristic.

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Keywords

algorithm
 
ant-colony optimization
 
greedy heuristic
 
leaf-constrained minimum spanning tree
 
leaf-constrained spanning tree
 
metaheuristic approaches
 
new approaches
 
new metaheuristic approaches
 
problem —
 
proposed genetic algorithm
 
spanning tree
 
spanning trees
 
subset-coded genetic algorithm
 
tabu search
 
weighted graph