Telecommunications Network Design Decision: A Genetic Algorithm Approach

Authors: G. Premkumar, Chao-Hsien Chu

The design and development of the network infrastructure to support mission-critical applications has become a critical and complex activity. This study explores the use of genetic algorithms (GA) for network design in the context of degree constrained minimal spanning tree (DCMST) problem, compares the performance of GA with a mathematical model that provides optimal solutions, and compares GA's performance with two heuristic methods for larger networks. Two performance measures, solution quality and computation time, are used for evaluation. The algorithms are evaluated on a wide variety of network sizes with both static and dynamic degree constraints on the network nodes. The results indicate that GA provides optimal solutions for small networks. For larger networks it provides better solution quality compared to heuristics, but is worse than heuristics in computation time.