William F. Kraus

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— We present results from a study comparing a recently developed coevolutionary genetic algorithm (CGA) against a set of evolutionary algorithms using a suite of multiobjective optimization benchmarks. The CGA embodies competitive coevolution and employs a simple, straightforward target population representation and fitness calculation based on(More)
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 antemm representation. The fitness calculation allows the implicit(More)
We present optimization results obtained for two type of antennas using evolutionary algorithms. A quadrifilar helical UHF antenna is currently flying aboard NASA's Mars Odyssey spacecraft and is due to reach final Martian orbit insertion in January, 2002. Using this antenna as a benchmark, we ran experiments employing a coevolutionary genetic algorithm to(More)
This article surveys the research of the Evolvable Systems Group at NASA Ames Research Center. Over the past few years, our group has developed the ability to use evolutionary algorithms in a variety of NASA applications ranging from spacecraft antenna design, fault tolerance for programmable logic chips, atomic force field parameter fitting, analog circuit(More)
the application and complexity of microelectromechanical (MEMS) devices increases, there is a corresponding need for automated design and optimization tools to augment engineers' design skills. Evolutionary computation provides a set of tools that may prove very effective in this application domain. Here we present a novel evolutionary computation encoding(More)
Because of their small size and high reliability, microelectromechani-cal (MEMS) devices have the potential to revolution many areas of engineering. As with conventionally-sized engineering design, there is likely to be a demand for the automated design of MEMS devices. This paper describes our current status as we progress toward our ultimate goal of using(More)
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