.png){kind=icon}
返回
Multifidelity surrogates-assisted multi-objective particle swarm algorithm for offline data-driven optimization
.png){kind=icon}
PRE
AI
DOI：10.1007/s10489-024-05612-w.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Surrogate-assisted evolutionary algorithms have been widely employed to solve data-driven optimization problems. However, for offline data-driven optimization, it is very challenging to perform evolutionary search efficiently as well as accurately since no new data is available during the optimization process. To mitigate this issue, a multifidelity surrogates-assisted multi-objective particle swarm optimization (MFSa-PSO) algorithm is proposed in this paper. First, two low-fidelity models with convergence and diversity characteristics separately and a high-fidelity model are constructed to assemble multifidelity surrogate models. Second, by adopting the knowledge transfer strategy, the multifidelity surrogates-assisted two-archive multi-objective particle swarm optimization is conducted to search optimal solutions more exactly and effectively. Third, the output solution set is achieved by associating the solutions of two archives with reference vectors. Finally, the proposed MFSa-PSO is compared with some popular surrogate-assisted evolutionary algorithms on benchmark problems to verify its effectiveness and outperformance. Additionally, a real-world application of the municipal solid waste incineration process is carried out to verify the engineering applicability of MFSa-PSO.
Keyword:
Offline data-driven optimization
Multifidelity surrogate models
Knowledge transfer
Two-archive multi-objective particle swarm optimization
Reference vectors
期刊
IF:
3.5
论文数:
7.6K
被引数:
1.7W
机构
引用论文
A Kriging-Assisted Two-Archive Evolutionary Algorithm for Expensive Many-Objective Optimization
.png){kind=icon}
PREAI
分享收藏
PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective OptimizationPlatEMO: 用于进化多目标优化的MATLAB平台
OAAI
OAAI分享收藏Data-Driven Surrogate-Assisted Multiobjective Evolutionary Optimization of a Trauma System创伤系统的数据驱动代理辅助多目标进化优化OAAI
OAAI分享收藏
查看更多内容