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 environment...

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Veröffentlicht in:IEEE transactions on antennas and propagation 2004-04, Vol.52 (4), p.1007-1014
Hauptverfasser: Coleman, C.M., Rothwell, E.J., Ross, J.E.
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Rothwell, E.J.
Ross, J.E.
description 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.
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subjects Algorithms
Antennas
Antennas and propagation
Computational modeling
Genetic algorithms
Microcontrollers
Optimization
Receiving antennas
Search algorithms
Searching
Shape
Simulated annealing
Switches
Testing
Wires
title Investigation of Simulated annealing, ant-colony optimization, and genetic algorithms for self-structuring antennas
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