| Article ID: | iaor1999354 |
| Country: | United Kingdom |
| Volume: | 25 |
| Issue: | 3 |
| Start Page Number: | 229 |
| End Page Number: | 237 |
| Publication Date: | Mar 1998 |
| Journal: | Computers and Operations Research |
| Authors: | Gen Mitsuo, Zhou Gengui |
| Keywords: | heuristics |
In this paper we present a new approach to solve the quadratic minimum spanning tree (q-MST) problem by using a genetic algorithm (GA). A skillful encoding for trees, denoted by Prüfer number, is adopted for GA operation. On comparing with the existing heuristic algorithms by 17 randomly generated numerical examples from 6-vertex graph to 50-vertex graph, the new GA approach shows its high effectiveness in solving the q-MST problem and real value in the practical network optimization.