Structural bias in differential evolution: A preliminary study

This paper extends the study of structural bias in popular metaheuristic global optimisation methods. Previously, it has been shown that both Genetic Algorithms and Particle Swarm Optimisation suffer from such bias. This means that difficulties already posed for a structurally biased algorithm by the fitness landscape itself are further unnecessarily exacerbated by the unexpected oversampling of some regions of the search space and avoidance of the others, to potential great detriment of the overall optimisation performance. Such bias is inherent in the core design of the algorithm. After careful examination, the authors conclude that some variants of Differential Evolution are not free of the structural bias. However, investigation suggests that the mechanisms of the formation of structural bias in Differential Evolution is different and can be balanced through a more careful design.This paper extends the study of structural bias in popular metaheuristic global optimisation methods. Previously, it has been shown that both Genetic Algorithms and Particle Swarm Optimisation suffer from such bias. This means that difficulties already posed for a structurally biased algorithm by the fitness landscape itself are further unnecessarily exacerbated by the unexpected oversampling of some regions of the search space and avoidance of the others, to potential great detriment of the overall optimisation performance. Such bias is inherent in the core design of the algorithm. After careful examination, the authors conclude that some variants of Differential Evolution are not free of the structural bias. However, investigation suggests that the mechanisms of the formation of structural bias in Differential Evolution is different and can be balanced through a more careful design.