CCE Faculty Articles
A Genetic Algorithm for the Constrained Forest Problem
Document Type
Article
Publication Title
ACEEE International Journal on Information Technology
ISSN
2158-012X
Publication Date
12-2011
Abstract
Given a graph with positive edge weights and a positive integer m, the Constrained Forest Problem (CFP) problem seeks a minimum-weight spanning subgraph each of whose components contains at least m vertices. Such a subgraph is called an m-forest. We present a genetic algorithm (GA) for CFP, which is NP-hard for me”4. Our GA evolves good spanning trees, as determined by the weight of the m-forest into which it can be partitioned by a simple greedy algorithm. Genetic operators include mutation, which replaces a spanning tree edge by a different edge that connects the same pair of components, and recombination, which combines the edge sets of two spanning trees to produce two new spanning trees. The GA discovers m-forests that are significantly better than those identified by best-known approximation algorithms for CFP, and identifies optimal solutions in small problems.
DOI
01.IJIT.01.03.8
Volume
1
Issue
3
First Page
47
Last Page
51
NSUWorks Citation
Laszlo, Michael J. and Mukherjee, Sumitra, "A Genetic Algorithm for the Constrained Forest Problem" (2011). CCE Faculty Articles. 525.
https://nsuworks.nova.edu/gscis_facarticles/525