Multiobjective differential evolution algorithm based on angle neighbourhood
Abstract：To solve the multiobjective optimization problem by differential evolution algorithm, a multiobjective d-ifferential evolution algorithm based on angle neighborhood is proposed. The weak domination is introduced to obtain the capacity of solving the multiobjective optimization problem. The neighbourhood of each individual is determined by computing the angle between each individual and weight vector in the objective space. To ensure the evolutionary direc-tion of individual, the mutation strategy based on angle neighbourhood is introduced to execute the mutation operation in angle neighborhood. Additionally, an external archive is established to save the non-dominated solutions obtained in evolutionary process. The archive is maintained regularly, and the distributivity of the approximate set has been greatly improved. A large amount of experimental results show that the neighbourhood determined by angle is more effective than the neighbourhood determined by Euclidean distance, and the convergence and distribution of the approximate set obtained by the proposed algorithm are obviously superior to multiobjective evolutionary algorithm based on decomposition and differential evolution (MOEA/D-DE) and nondominated sorting genetic algorithmⅡ(NSGAⅡ).
Keywords：differential evolutionangle neighbourhoodexternal archivemultiobjective optimization
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：11( 22-32 )