Adaptive Particle Swarm Optimization with Local Search for Multi-robot Multi-point Dynamic Aggregation-Reference-Cited by-同舟云学术

Adaptive Particle Swarm Optimization with Local Search for Multi-robot Multi-point Dynamic Aggregation

Published:2023-07-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Companion Conference on Genetic and Evolutionary Computation
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Author:

Dai Shihao¹²^ORCID,Jia Ya-Hui¹²^ORCID,Chen Wei-Neng¹^ORCID,Mei Yi³^ORCID

Affiliation:

1. South China University of Technology, Guangzhou, China

2. Pazhou Lab, Guangzhou, China

3. Victoria University of Wellington, Wellington, New Zealand

Funder

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

The Fundamental Research Funds for the Central Universities

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583133.3590586

Reference10 articles.

1. Adaptive Coordination Ant Colony Optimization for Multipoint Dynamic Aggregation

2. A Memetic Algorithm for the Task Allocation Problem on Multi-robot Multi-point Dynamic Aggregation Missions

3. Guanqiang Gao , Bin Xin , Yi Mei , Shengyu Lu , and Shuxin Ding . 2022 . A multiobjective evolutionary algorithm with new reproduction and decomposition mechanisms for the multi-point dynamic aggregation problem . In Proceedings of the Genetic and Evolutionary Computation Conference. 1182--1190 . Guanqiang Gao, Bin Xin, Yi Mei, Shengyu Lu, and Shuxin Ding. 2022. A multiobjective evolutionary algorithm with new reproduction and decomposition mechanisms for the multi-point dynamic aggregation problem. In Proceedings of the Genetic and Evolutionary Computation Conference. 1182--1190.

4. A memetic level-based learning swarm optimizer for large-scale water distribution network optimization

5. Asif Khan , Bernhard Rinner , and Andrea Cavallaro . 2016. Cooperative robots to observe moving targets . IEEE transactions on cybernetics 48, 1 ( 2016 ), 187--198. Asif Khan, Bernhard Rinner, and Andrea Cavallaro. 2016. Cooperative robots to observe moving targets. IEEE transactions on cybernetics 48, 1 (2016), 187--198.