Comparative Results: Group Search Optimizer and Central Force Optimization

This note compares the performance of two multidimensional search and optimization algorithms: Group Search Optimizer and Central Force Optimization. GSO is a new state-of-theart algorithm that has gained some notoriety, consequently providing an excellent yardstick for measuring the performance of other algorithms. CFO is a novel deterministic metaheuristic that has performed well against GSO in previous tests. The CFO implementation reported here includes architectural improvements in errant probe retrieval and decision space adaptation that result in even better performance. Detailed results are provided for the twenty-three function benchmark suite used to evaluate GSO. CFO performs better than or essentially as well as GSO on twenty functions and nearly as well on one of the remaining three. Ver. 3, 24 February 2010 (Fig. A2(b) replaced for improved visualization; minor typos corrected). Ver. 2, 22 February 2010 (Reset of decision space boundaries to initial values after time loop explicitly added in Fig. 1 because previously it was implied but explicitly included only in the source code listing in Appendix 3; Fig. A2(b) and discussion added to provide 3D IPD visualization; Reference [6] updated). 14 February 2010 Saint Augustine, Florida