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This note compares the performance of two multidimensional search andoptimization algorithms: Group Search Optimizer and Central Force Optimization.GSO is a new state-of-the-art algorithm that has gained some notoriety,consequently providing an excellent yardstick for measuring the performance ofother algorithms. CFO is a novel deterministic metaheuristic that has performedwell against GSO in previous tests. The CFO implementation reported hereincludes architectural improvements in errant probe retrieval and decisionspace adaptation that result in even better performance. Detailed results areprovided for the twenty-three function benchmark suite used to evaluate GSO.CFO performs better than or essentially as well as GSO on twenty functions andnearly as well on one of the remaining three. Includes update 24 February 2010.

Comparative Results: Group Search Optimizer and Central Force Optimization