Tutorial: Selection, Exploration and Exploitation

The goal of exploration is to seek out new areas of the search space. The effect of selection is to concentrate search around the best-known areas of the search space. The power of selection can overwhelm exploration, allowing it to turn any exploratory method into a hill climber. The balancing of exploration and exploitation requires more than the consideration of what solutions are created -- it requires an analysis of the interplay between exploration and selection. This tutorial reviews a broad range of selection methods used in metaheuristics. Novel tools to analyze the effects of selection on exploration in the continuous domain are introduced and demonstrated on Particle Swarm Optimization and Differential Evolution. The difference between convergence (no exploratory search solutions are created) and stall (all exploratory search solutions are rejected) is highlighted. Remedies and alternate methods of selection are presented, and the ramifications for the future design of metaheuristics are discussed.