Local Descent Direction Vector-Based Differential Evolution for Multiobjective Optimization

Differential evolution (DE) is an effective optimization method for global continuous optimization problems. Recently, we developed local descent direction vector based differential evolution (LDDVDE), which uses local descent direction vectors based on the operation vectors in order to improve the local search performance of DE. In this paper, we extend LDDVDE to multiobjective optimization problems. We adopt the hyper-volume indicator to order the operation vectors to make the local descent direction vectors for the case of multiobjective optimization problems. The effectiveness of the proposed method is confirmed through some numerical experiments for typical benchmark problems.