Using bliss points to enhance direction based multi-objective algorithms

Abstract

Using improvement direction to control the evolution of multi-objective optimization algorithms is an interesting and effective method. Improvement direction techniques often evaluate the geometric properties of the solution set in the objective space and based on that to adjusting the evolutionary process to ensure it is capable of exploration and exploitation. The direction of improvement is usually determined based on the convergent and diverse nature of the solution population, in fact, the distribution of the solution population can suggest an online adjustment of the evolutionary process to overcome the problem of keeping the balance between convergence and diversity. In this study, we identify empty regions in the solution population and use the centers of those areas, which we call bliss points, to direct and adjust the algorithms which use improvement direction to enhance the quality of the algorithms. Experimental results have shown competitive results, promising to apply to multi-objective evolutionary algorithms using other geometric techniques.