Double space based multiobjective evolutionary algorithm

Recently, solving multiobjective problems are gaining more and more attention due to its useful applications in the area of engineering, bioinformatics, pattern recognition. Although there exist a lot of multiobjective evolutionary algorithms (MOEAs) for solving multiobjective problems, few of them considers the evolutionary process in both the solution space and the objective space. In the paper, we will propose a new hybrid multiobjective evolutionary algorithm named as double space based multiobjective evolutionary algorithms (DS-MOEA) to perform multiobjective optimization. Compared with traditional MOEAs, DS-MOEA not only considers the evolutionary process in the solution space, but also takes into account the knowledge learning process in the objective space. The results in the experiment illustrate that DS-MOEA works well during the process of solving multiobjective problems.