@inproceedings{596840839bee46b59477818f2f301770,
title = "A cone order sequence based multi-objective evolutionary algorithm",
abstract = "A cone order sequence based MOEA (CS-MOEA) is proposed to deal with the multi-objective optimization problems. Instead of only using the Pareto dominance, it constructs a sequence of cone order to balance the search diversity and convergence. By gradually increasing the open angle of the cone order, it approximates the Pareto cone gradually. A simple formula for judging the θ-cone dominance is derived, which is easy to be computed. Moreover, an energy model is introduced for the selection of individuals to maintain population diversity. Experiments on more than 10 problems (i.e. zdt and dtlz benchmark problem sets) demonstrate that the proposed method is competitive, compared with Stable Matching MOEA/D (STM-MOEA/D) and MOEA/D-DE.",
keywords = "DECOMPOSITION, OPTIMIZATION, HYPERVOLUME, SELECTION, DIVERSITY",
author = "Yueming Lyu and Qingfu Zhang and Ka-Chun Wong",
year = "2016",
month = nov,
day = "14",
doi = "10.1109/CEC.2016.7744056",
language = "English",
isbn = "9781509006229",
series = "IEEE Congress on Evolutionary Computation",
publisher = "IEEE",
pages = "2169--2176",
booktitle = "2016 IEEE Congress on Evolutionary Computation, CEC 2016",
address = "United States",
note = "2016 IEEE Congress on Evolutionary Computation, CEC 2016 ; Conference date: 24-07-2016 Through 29-07-2016",
}