A surrogate-assisted multi-objective particle swarm optimization of expensive constrained combinatorial optimization problems

标题
A surrogate-assisted multi-objective particle swarm optimization of expensive constrained combinatorial optimization problems
作者
关键词
Data-driven optimization, Constrained combinatorial optimization, Expensive problems, Multi-objective particle swarm optimization (MOPSO), Surrogate model, Random forest
出版物
KNOWLEDGE-BASED SYSTEMS
Volume 223, Issue -, Pages 107049
出版商
Elsevier BV
发表日期
2021-04-21
DOI
10.1016/j.knosys.2021.107049

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Find Funding. Review Successful Grants.

Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.

Explore

Become a Peeref-certified reviewer

The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.

Get Started