@inproceedings{07ce33102b964aa2a374ccd55a17d140,
title = "Heterogeneous Particle Swarm Optimizer and its Application in Aircraft Manufacturing Logistics",
abstract = "Particle swarm optimization (PSO) attracts much attention due to its ability in solving complex practical engineering problems effectively. To further improve its performance, a heterogeneous particle swarm optimizer (HPSO) is proposed in this work. Five widely used benchmark functions are selected to test its efficiency. Furthermore, five state-of-the-art improved PSO variants are selected for a comparisons purpose. The results demonstrate that HPSO is better than the other five algorithms. A logistics problem in aircraft manufacturing is then studied and solved. The results show HPSO's superiority over its tested PSO variants.",
keywords = "aircraft manufacturing logistics, evolutionary computation, facility location, particle swarm optimizer (PSO)",
author = "Yulian Cao and Mengchu Zhou and Wenfeng Li and Gabriel Lodewijks",
note = "Funding Information: This work was partly supported by the NSFC under Grant No. 61571336. Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020 ; Conference date: 30-10-2020 Through 02-11-2020",
year = "2020",
month = oct,
day = "30",
doi = "10.1109/ICNSC48988.2020.9238107",
language = "English (US)",
series = "2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020",
address = "United States",
}