TY - GEN
T1 - A decomposition based multiobjective evolutionary algorithm with classification
AU - LIN, Xi
AU - ZHANG, Qingfu
AU - KWONG, Sam
N1 - This work was supported by the National Natural Science Foundation of China under Grants 61473241.
PY - 2016/11/14
Y1 - 2016/11/14
N2 - This paper investigates how to use a pre-selection approach to improve the performance of the multiobjective evolutionary algorithm based on decomposition (MOEA/D). It proposes a novel MOEA/D algorithm with classification to serve this purpose. The proposed algorithm builds a classification model on the search space to filter all new generated solutions, and mainly evaluates those promising solutions for reducing real function evaluation costs during the search process. Experimental study on different test instances validates that the pre-selection approach can significantly improve the performance of a classical MOEA/D.
AB - This paper investigates how to use a pre-selection approach to improve the performance of the multiobjective evolutionary algorithm based on decomposition (MOEA/D). It proposes a novel MOEA/D algorithm with classification to serve this purpose. The proposed algorithm builds a classification model on the search space to filter all new generated solutions, and mainly evaluates those promising solutions for reducing real function evaluation costs during the search process. Experimental study on different test instances validates that the pre-selection approach can significantly improve the performance of a classical MOEA/D.
UR - http://www.scopus.com/inward/record.url?scp=85008256614&partnerID=8YFLogxK
U2 - 10.1109/CEC.2016.7744206
DO - 10.1109/CEC.2016.7744206
M3 - Conference paper (refereed)
SP - 3292
EP - 3299
BT - 2016 IEEE Congress on Evolutionary Computation, CEC 2016
ER -