Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
A Comparison of Dynamic Fitness Schedules for Evolutionary Design of Amplifiers
EH '99 Proceedings of the 1st NASA/DOD workshop on Evolvable Hardware
Automated design and optimization of wire antennas using genetic algorithms
Automated design and optimization of wire antennas using genetic algorithms
A circuit representation technique for automated circuit design
IEEE Transactions on Evolutionary Computation
Innately adaptive robotics through embodied evolution
Autonomous Robots
ARO: A new model-free optimization algorithm inspired from asexual reproduction
Applied Soft Computing
Expert Systems with Applications: An International Journal
Causally-guided evolutionary optimization and its application to antenna array design
Integrated Computer-Aided Engineering
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Yagi-Uda antennas are known to be difficult to design and optimize due to their sensitivity at high gain, and the inclusion of numerous parasitic elements. We present a genetic algorithm-based automated antenna optimization system that uses a fixed Yagi-Uda topology and a byte-encoded antenna representation. The fitness calculation allows the implicit relationship between power gain and sidelobe/backlobe loss to emerge naturally, a technique that is less complex than previous approaches. The genetic operators used are also simpler. Our results include Yagi-Uda antennas that have excellent bandwidth and gain properties with very good impedance characteristics. Results exceeded previous Yagi-Uda antennas produced via evolutionary algorithms by at least 7.8% in mainlobe gain. We also present encouraging preliminary results where a coevolutionary genetic algorithm is used.