A Dimensional Diversity Based Hybrid Multiobjective Evolutionary Algorithm for Optimization Problem

作者：Wang, Peng; Zhang, Changsheng^*; Zhang, Bin; Liu, Tingting; Wu, Jiaxuan

来源：International Journal of Pattern Recognition and Artificial Intelligence, 2016, 30(7): 1659020.

DOI：10.1142/S0218001416590205

• Artificial intelligence
• evolutionary algorithm
• fireworks explosion
• dimensional diversity
• solution density

Multiobjective density driven evolutionary algorithm (MODdEA) has been quite successful in solving multiobjective optimization problems (MOPs). To further improve its performance and address its deficiencies, this paper proposes a hybrid evolutionary algorithm based on dimensional diversity (DD) and firework explosion (FE). DD is defined to reflect the diversity degree of population dimension. Based on DD, a selection scheme is designed to balance diversity and convergence. A hybrid variation based on FE and genetic operator is designed to facilitate diversity of population. The proposed algorithm is tested on 14 tests problems with diverse characteristics and compared with three state-of-the-art designs. Experimental results show that the proposed design is better or at par with the chosen state-of-the-art algorithms for multiobjective optimization.

• 出版日期2016-8
• 单位东北大学