Central Force Optimization Applied to the PBM Suite of Antenna Benchmarks

Abstract: Central Force Optimization (CFO) is a new nature-inspired deterministic multi-dimensional search and optimization metaheuristic based on the metaphor of gravitational kinematics. CFO is applied to the PBM antenna benchmark suite and the results compared to published performance data for other optimization algorithms. CFO acquits itself quite well. CFO's gradient-like nature is discussed, and it is speculated that a "generalized hyperspace derivative" might be defined for optimization problems as a new mathematical construct based on the Unit Step function. What appears to be a sufficient but not necessary condition for local trapping, oscillation in the probe average distance curve, is discussed in the context of the theory of gravitational "resonant returns" that gives rise to strikingly similar oscillatory curves. It is suggested that the theory may be applicable to CFO as an aid to understanding trapping and to developing effective mitigation techniques, possibly based on a concept of "energy" in CFO space. It also is suggested that CFO may be re-formulated as a "total energy" model by analogizing conservation of energy for orbiting masses in physical space.