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Bees algorithm for degree-constrained minimum spanning tree problem

Authors: Meenakshi Malik;

Bees algorithm for degree-constrained minimum spanning tree problem

Abstract

The problem of identifying a minimum spanning tree (MST) of a connected, undirected graph is a classical combinatorial optimization problem which can be solved efficiently in polynomial time by greedy heuristics. But, there are several practically relevant variants of MST problem that have been shown to be NP-complete. One of the variants of MST considered in this work is degree-constrained spanning tree. Recently, most of the works on this problem focus on heuristics that can find good solutions in a reasonable amount of time. In this paper, we have proposed an approach based on bees algorithm procedure to handle the degree constrained problem. A travel salesman problem is considered and a set of 2-degree spanning trees are extracted from the graph and supplied to the proposed algorithm. A bees algorithm-based approach is carried out to optimize the spanning trees based on their cost values. The fitness function points the cost effective degree constrained spanning tree. Experimentation of the proposed approach is carried out on a traveling salesman problem. The results showed that the proposed approach has produces cost effective and time effective results.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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