Parameter-Free Deterministic Global Search with Central Force Optimization

This note describes a parameter-free implementation of Central Force Optimization for deterministic multidimensional search and optimization. The user supplies only one input: the objective function to be maximized, nothing more. The CFO equations of motion are simplified by assigning specific values to CFO’s basic parameters, and this particular algorithmic implementation also includes hardwired internal parameters so that none is user-specified. The algorithm’s performance is tested against a widely used suite of twenty three benchmark functions and compared to other state-of-the-art algorithms. CFO performs very well indeed. 4 March 2010 Ver. 2, 20 March 2010 [A. Corrects typographical error in pseudocode in Fig. 1. “Very large” negative number should be 4200 10 − as shown in the source code listing on page 17 instead of 4200 10 − as shown in error in the original version. B. Adds discussion after equation (1) for the case p j k j R R 1 1 − − = r r and modifies source code listing at the top of page 18 accordingly.]