Telecommunications network design - Comparison of alternative approaches

G. Premkumar, Chao Hsien Chu, Hsinghua Chou

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


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 for small networks the performance of GA with a mathematical model that provides optimal solutions; and for larger networks, compares GA's performance with two heuristic methods - edge exchange and primal algorithm. 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 edge exchange and primal method, but is worse than the two methods in computation time.

Original languageEnglish (US)
Pages (from-to)483-506
Number of pages24
JournalDecision Sciences
Issue number2
StatePublished - 2000

All Science Journal Classification (ASJC) codes

  • General Business, Management and Accounting
  • Strategy and Management
  • Information Systems and Management
  • Management of Technology and Innovation


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