@inproceedings{ee2a7b305cd44bf68927ec17c3bb0d05,
title = "Particle Swarm Optimizer Without Communications Among Particles",
abstract = "Particle Swarm Optimizer (PSO) is a kind of population-based evolutionary optimizer. Many PSO variants have been proposed and most of them require mutual communications among particles for their fitness values to find the best position, hence leading to their effective collaboration. However, some real scenes using swarm robots to perform PSO cannot provide reliable communications during their distributed search. To handle such issues, this work proposes a novel PSO variant without communications among particles, called Communication-free Particle Swarm Optimizer (CfPSO). It employs particles{\textquoteright} detection ability instead of direct communications among them to accomplish the needed collaboration. Experimental results show that it obtains higher accurate performance than the standard PSO equipped with full communication ability, which is against human intuition.",
keywords = "Communication, Communication-free, Particle Swarm Optimizer",
author = "Zhang, {Jun Qi} and Huang, {Xu Rui} and Huan Liu and Zhou, {Meng Chu}",
note = "Funding Information: This work was supported by Innovation Program of Shanghai Municipal Education Commission (202101070007E00098), Shanghai Industrial Collaborative Science and Technology Innovation Project (2021-cyxt2-kj10), Shanghai Municipal Science and Technology Major Project (2021SHZDZX0100) and the Fundamental Research Funds for the Central Universities. This work was also supported in part by the National Natural Science Foundation of China (51775385, 61703279, 62073244 and 61876218), and the Shanghai Innovation Action Plan under grant no. 20511100500. Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 14th International Conference on Advances in Swarm Intelligence, ICSI 2023 ; Conference date: 14-07-2023 Through 18-07-2023",
year = "2023",
doi = "10.1007/978-3-031-36622-2_13",
language = "English (US)",
isbn = "9783031366215",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "158--167",
editor = "Ying Tan and Yuhui Shi and Wenjian Luo",
booktitle = "Advances in Swarm Intelligence - 14th International Conference, ICSI 2023, Proceedings",
address = "Germany",
}