Abstract
This paper investigates the effect of adding three extensions to Central Force Optimization when it is used as the Global Search and Optimization method for the design and optimization of 6-elementYagi-Uda arrays. Those extensions are Negative Gravity, Elitism, and Dynamic Threshold Optimization. The basic CFO heuristic does not include any of these, but adding them substantially improves the algorithm’s performance. This paper extends the work reported in a previous paper that considered only negative gravity and which showed a significant performance improvement over a range of optimized arrays. Still better results are obtained by adding to the mix Elitism and DTO. An overall improvement in best fitness of 19.16% is achieved by doing so. While the work reported here was limited to the design/optimization of 6- element Yagis, the reasonable inference based on these data is that any antenna design/optimization problem, indeed any Global Search and Optimization problem, antenna or not, utilizing Central Force Optimization as the Global Search and Optimization engine will benefit by including all three extensions, probably substantially.
Highlights
IntroductionIn a previous paper, [1], six element Yagi-Uda arrays (Yagis) were optimally de-
This paper investigates the effect of adding three extensions to Central Force Optimization when it is used as the Global Search and Optimization method for the design and optimization of 6-elementYagi-Uda arrays
This paper extends the work reported in a previous paper that considered only negative gravity and which showed a significant performance improvement over a range of optimized arrays
Summary
In a previous paper, [1], six element Yagi-Uda arrays (Yagis) were optimally de-. CFO searches for the maxima of an objective function, not its minima. The effect of negative gravity is to improve CFO’s exploration of the decision space (DS) by causing probes that otherwise would coalesce around discovered maxima to disperse away from those maxima and sample under-sampled regions or perhaps regions that were not sampled at all. Based on the results reported in [1] there is no question that all CFO implementations and applications likely will benefit from some measure of negative gravity. At a minimum the algorithm’s performance should be investigated with this added extension
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