On the Utility of Directional Information for Repositioning Errant Probes in Central Force Optimization

Central Force Optimization is a global search and optimization algorithm that searches a decision space by flying "probes" whose trajectories are deterministically computed using two equations of motion. Because it is possible for a probe to fly outside the domain of feasible solutions, a simple errant probe retrieval method has been used previously that does not include the directional information contained in a probe's acceleration vector. This note investigates the effect of adding directionality to the "repositioning factor" approach. As a general proposition, it appears that doing so does not improve convergence speed or accuracy. In fact, adding directionality to the original errant probe retrieval scheme appears to be highly inadvisable. Nevertheless, there may be alternative probe retrieval schemes that do benefit from directional information, and the results reported here may assist in or encourage their development.Comment: Ver. 2, 6 June 2010 (Fig. 1 improved for clarity; minor typos corrected

Dynamic Threshold Optimization - A New Approach?

Dynamic Threshold Optimization (DTO) adaptively "compresses" the decision space (DS) in a global search and optimization problem by bounding the objective function from below. This approach is different from "shrinking" DS by reducing bounds on the decision variables. DTO is applied to Schwefel's Problem 2.26 in 2 and 30 dimensions with good results. DTO is universally applicable, and the author believes it may be a novel approach to global search and optimization.Comment: Rev. 05 June 2012: Typos & reference [1] corrected. Material adde

A novel methodology for antenna design and optimization: Variable Zo

This paper describes "Variable Zo," a novel and proprietary approach to antenna design and optimization. The new methodology is illustrated by applying it to the design of a resistively-loaded bowtie antenna and to two broadband Yagi-Uda arrays. Variable Zo is applicable to any antenna design or optimization methodology. Using it will result in generally better antenna designs across any user-specified set of performance objectives.Comment: Ver. 2 (14 July 2011). Adds Yagi-Uda array design example. Updates source cod

Issues in Antenna Optimization - A Monopole Case Study

A typical antenna optimization design problem is presented, and various issues involved in the design process are discussed. Defining a suitable objective function is a central question, as is the type of optimization algorithm that should be used, stochastic versus deterministic. These questions are addressed by way of an example. A single-resistor loaded broadband HF monopole design is considered in detail, and the resulting antenna compared to published results for similar continuously loaded and discrete resistor loaded designs.Comment: Ver. 2. Corrects formatting in Table 1, updates references, and adds source code in Appendi