A New Dominance Relation-Based Evolutionary Algorithm for Many-Objective Optimization

Many-objective optimization has posed a great challenge to the classical Pareto dominance-based multiobjective evolutionary algorithms (MOEAs). In this paper, an evolutionary algorithm based on a new dominance relation is proposed for many-objective optimization. The proposed evolutionary algorithm aims to enhance the convergence of the recently suggested nondominated sorting genetic algorithm III by exploiting the fitness evaluation scheme in the MOEA based on decomposition, but still inherit the strength of the former in diversity maintenance. In the proposed algorithm, the nondominated sorting scheme based on the introduced new dominance relation is employed to rank solutions in the environmental selection…

• NN
  National Natural Science Foundation of China

  Awards: 2012CB316301, 61305079, 61329302, 61175110
• CS
  China Scholarship Council
• EA
  Engineering and Physical Sciences Research Council

  Awards: EP/J017515, Grant EP/J017515/1, EP/J017515/1, EP/J017515/1
• NK
  National Key Research and Development Program of China

  Award: 2012CB316301