@inproceedings{fa8f028677dc4463a774fa6ae1bfef08,
title = "Balancing exploration and exploitation in multiobjective evolutionary optimization",
abstract = "Balancing exploration and exploitation is fundamental to the performance of an evolutionary algorithm. In this paper, we propose a survival analysis method to address this issue. Results of the analysis is used to adaptively choose appropriate new solution creation operators which prefer either exploration or exploitation. In the developed algorithm, a differential evolution recombination operator is used for the exploration purpose, while a new clustering-based operator is proposed for exploitation. Empirical comparison with four well-known multi-objective evolutionary algorithms on test instances with complex Pareto sets and Pareto fronts indicates the effectiveness and outperformance of the developed algorithms on these test instances in terms of commonly-used metrics.",
keywords = "Exploitation, Exploration, Multiobjective optimization",
author = "Jianyong Sun and Qingfu Zhang and Hu Zhang and Huanhuan Chen",
note = "Publisher Copyright: {\textcopyright} 2018 Copyright held by the owner/author(s).; 2018 Genetic and Evolutionary Computation Conference, GECCO 2018 ; Conference date: 15-07-2018 Through 19-07-2018",
year = "2018",
month = jul,
day = "6",
doi = "10.1145/3205651.3205708",
language = "英语",
series = "GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion",
publisher = "Association for Computing Machinery, Inc",
pages = "199--200",
booktitle = "GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion",
}