Improving Evolutionary Algorithms in a Continuous Domain by Monitoring the Population Midpoint
Author:
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computational Theory and Mathematics,Theoretical Computer Science,Software
Link
http://xplorestaging.ieee.org/ielx7/4235/8053848/07862754.pdf?arnumber=7862754
Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Population Midpoint-Based Differential Evolution for Localization in Wireless Sensor Networks;2022 IEEE Globecom Workshops (GC Wkshps);2022-12-04
2. A Version of NL-SHADE-RSP Algorithm with Midpoint for CEC 2022 Single Objective Bound Constrained Problems;2022 IEEE Congress on Evolutionary Computation (CEC);2022-07-18
3. A hypervolume distribution entropy guided computation resource allocation mechanism for the multiobjective evolutionary algorithm based on decomposition;Applied Soft Computing;2022-02
4. HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space;2021 IEEE Symposium Series on Computational Intelligence (SSCI);2021-12-05
5. A New Step-Size Adaptation Rule for CMA-ES Based on the Population Midpoint Fitness;2021 IEEE Congress on Evolutionary Computation (CEC);2021-06-28
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