Correlative Selection Mechanism-based Evolutionary Algorithm for Many-objective Optimization
PAN Xiaoying
LI Angru
CHEN Xuejing
ZHAO Qian
Abstract：In the field of scientific research are widespread high-dimensional multi-objective optimization problem and diffi-cult to have a better solution.Correlative selection mechanism-based evolutionary algorithm for many-objective optimization is pro-posed. First,the mutation algorithm is using finite difference algorithm to guide operator and it is using crossover operator to im-prove the search ability and search accuracy;Then,the algorithm does not adopt the traditional non dominated sorting selection mechanism,but selecting individuals based on the correlation is used to maintain the diversity of population.Some standard bench-mark problems are tested to demonstrate the effectiveness of the algorithm.Experimental results show that the algorithm performes better than other algorithms in convergence and diversity.
Keywords：high-dimensional multi-objective optimizationdifference operatormutation operatorcorrelative selection
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 711-716,731 )