An orthogonal multi-objective evolutionary algorithm with lower-dimensional crossover

  • Authors:

  • Song Gao;Sanyou Zeng;Bo Xiao;Lei Zhang;Yulong Shi;Xin Tian;Yang Yang;Haoqiu Long;Xianqiang Yang;Danping Yu;Zu Yan

  • Affiliations:

  • School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...;School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...;School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...;School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...;School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...;School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...;School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...;School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...;School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...;School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...;School of Computer Science, Research Centre for Space Science & Technology and The State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, C ...

  • Venue:
  • CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper proposes an multi-objective evolutionary algorithm. The algorithm is based on OMOEA-II[2]. A new linear breeding operator with lower-dimensional crossover and copy operation is used. By using the lower-dimensional crossover, the complexity of searching is decreased so the algorithm converges faster. The orthogonal crossover increase probability of producing potential superior solutions, which helps the algorithm get better results. Ten unconstrained problems in [1] are used to test the algorithm. For three problems, the obtained solutions are very close to the true Pareo Front, and for one problem, the obtained solutions distribute on part of the true Pareo Front.