A Simple and Effective Termination Condition for Both Single- and Multi-Objective Evolutionary Algorithms

被引:0
作者
Kukkonen, Saku [1 ]
Coello Coello, Carlos A. [2 ]
机构
[1] Univ Eastern Finland, Sch Comp, Machine Learning Grp, Kuopio, Finland
[2] UAM Azcapotzalco, Dept Sistemas, Mexico City, DF, Mexico
来源
2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2019年
基金
芬兰科学院;
关键词
GENERALIZED DIFFERENTIAL EVOLUTION; NON-DOMINATED SOLUTIONS; PERFORMANCE ASSESSMENT; STOPPING CRITERION; OPTIMIZATION; DESIGN; SET;
D O I
10.1109/cec.2019.8790292
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, a simple and effective termination condition for both single- and multi-objective evolutionary algorithms has been proposed. The termination condition is based on simply observing objective values of solution candidates during generations. Effectiveness of the termination condition is self-evident with single-objective problems but unclear with multiobjective problems. Therefore, experiments with some well known bi- and tri-objective test problems have been performed. The proposed termination condition is implemented in Generalized Differential Evolution (GDE) that is a general purpose optimization algorithm for both single- and multi-objective optimization with or without constraints. Our preliminary results indicate that the proposed termination condition is a suitable termination condition also with multi-objective problems. With the termination condition and a control parameter adaptation technique previously introduced, GDE has become a fully automated optimization algorithm that can be used by any optimization practitioner.
引用
收藏
页码:3053 / 3059
页数:7
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