Influence of Dimensionality and Population Size on Opposition-based Differential Evolution Using the Current Optimum

Diverse forms of opposition are already existent virtually everywhere around us and utilizing opposite numbers to accelerate an optimization method is a new idea. In this study, three algorithms (DE, COODE and IODE) are compared for different problem dimensions and different population sizes. Experiments on 58 widely used benchmark problems show that, opposition-based differential evolution using the current optimum performs better than the original algorithm for larger population size which is usually required for more complex and high-dimensional problems.