The radio network design problem (RNDP) can be automated by modeling it as a generalized Steiner tree-star (GSTS) problem. Any minimum Steiner tree (MST) solution to the GSTS problem directly identifies the radio tower locations and equipment needed to build the network at an optimal cost.

This project uses ant colony optimization (ACO) to solve the MST problem on GSTS graphs, and also provides a 2-approximation implementation for comparison.

This code was developed by Jeffrey Sharkey as part of his thesis work at Montana State University. His work was sponsored by the Western Transportation Institute, and was guided by advisor Doug Galarus. Other valuable guidance was provided by Dr. Bill Jameson and Gary Schoep.

This project is also based on the libprop radio propagation library, also developed by Jeffrey at MSU with the help of Doug Galarus, Dr. Bill Jameson, and Gary Schoep. Code for libprop can be found at: http://code.google.com/p/libprop/