Designing communication network topologies using steady-state genetic algorithms

Abstract

This article presents the application of steady state genetic algorithms (SSGA) to minimize the total installation cost of a communication network by optimally designing the topology layout and assigning the corresponding capacities (TDCA problem). This highly constrained optimization problem is shown to be better solved using GAs. A binary representation of links between node pairs is developed and tested on a network of 20 nodes. Improved results, both in terms of network cost, performance and computation speed, are obtained when comparing with existing heuristic approaches.