An exploration-only hybrid for large scale global optimization

Two factors affect the effectiveness of exploration, the bias introduced by selection and the concurrence of exploration and exploitation. The Leaders and Followers metaheuristic was designed to reduce the bias from selection by using a two-population scheme. Minimum Population Search was designed to limit the concurrence of exploration and exploitation through the use of Thresheld Convergence in its sampling strategy. This paper presents Unbiased Exploratory Search, which combines both approaches and simultaneously addresses the effects of these two factors. An exploration-only exploitation-only hybrid is then presented using Unbiased Exploratory Search for the exploration-only phase of the hybrid. The hybrid is tested on the CEC large scale optimization benchmark.