Investigation of simulated annealing, ant-colony optimization, and genetic algorithms for self-structuring antennas

A self-structuring antenna (SSA) is capable of arranging itself into a large number of configurations. Because the properties of the configurations are generally unknown at the onset of operation, efficient search algorithms are required to find suitable configurations for a given set of environmental and operational conditions. This paper investigates the use of ant-colony optimization, simulated annealing, and genetic algorithms for finding suitable antenna states. The implementation of each algorithm for SSA searches is described, and the performance of each algorithm is compared to a random search.