@inproceedings{8566b6d93c8d45f4b43001a145af68f4,
title = "A Cooperative Coevolutionary Algorithm for Multiobjective Optimization",
abstract = "This paper presents a kind of cooperative co-evolutionary algorithm (CCEA) for multi-objective optimization (MOO). In this algorithm, solutions evolve in the form of cooperative subpopulations. An archive stores non-dominated solutions and helps to evaluate individuals in the subpopulations. The mechanism of niching is applied to maintain the diversity of solutions in the archive. Meanwhile, an extending operator is designed to mine information on solution distribution from the archive and guide the search to regions that are not explored enough. Extensive simulations are performed on different benchmark problems for various multi-objective evolutionary algorithms (MOEAs) and indicate that CCEA is strongly competitive with five recent well-known MOEAs in finding a good non-dominated solution set. ",
keywords = "Co-evolution, Evolutionary algorithm, Multi-objective optimization",
author = "Tan, \{K. C.\} and Lee, \{T. H.\} and Yang, \{Y. J.\} and Liu, \{D. S.\}",
year = "2004",
month = oct,
doi = "10.1109/ICSMC.2004.1399965",
language = "English",
isbn = "0-7803-8566-7",
volume = "7",
publisher = "IEEE",
pages = "1926--1931",
booktitle = "2004 IEEE International Conference on Systems, Man and Cybernetics",
address = "United States",
note = "2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 ; Conference date: 10-10-2004 Through 13-10-2004",
}