A bi-population clan-based genetic algorithm for heat pipe-constrained component layout optimization

作者：

Highlights：

• It is a challenge to optimize component layout with heat dissipation on heat pipes.

• Bi-population strategy can alleviate the intractability by decomposing HCLO.

• Clan-based framework inspired by human evolution is proposed to tackle Many-optima.

• BCGA outperforms the competing algorithms in both effectiveness and efficiency.

摘要

•It is a challenge to optimize component layout with heat dissipation on heat pipes.•Bi-population strategy can alleviate the intractability by decomposing HCLO.•Clan-based framework inspired by human evolution is proposed to tackle Many-optima.•BCGA outperforms the competing algorithms in both effectiveness and efficiency.

论文关键词：Component layout optimization,Heat pipe,Genetic algorithm,Bi-population,Clan-based framework

论文评审过程：Received 16 July 2022, Revised 4 September 2022, Accepted 18 September 2022, Available online 24 September 2022, Version of Record 10 October 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118881