Hybrid Algorithm Research Based on Improved Genetic Algorithm and Auction Algorithm for AUVs Task Allocation

Guanfeng Ji, Zhuo Zhang, Guan Huang, Rongxin Cui, Weisheng Yan, Shouxu Zhang, Yintao Wang, Xinxin Guo, Qi Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In Autonomous Underwater Vehicles (AUVs) systems, an effective task allocation is crucial for AUVs to complete tasks cooperatively. To address the problems of low solution efficiency in static task allocation algorithms and poor real-time performance in dynamic task allocation algorithms, we present a hybrid algorithm based on the improved genetic algorithm and the auction algorithm. Specifically, the auction algorithm is applied to solve the initial solution of task allocation, then the improved genetic algorithm is applied to solve the problem on this basis. The hybrid algorithm can effectively improve the solution efficiency of static task allocation. In particular, our presented algorithm can meet the demands of dynamic task allocation. Finally, simulation results confirm the effectiveness of the proposed algorithm.

Original languageEnglish
Title of host publicationICARM 2024 - 2024 9th IEEE International Conference on Advanced Robotics and Mechatronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages88-93
Number of pages6
ISBN (Electronic)9798350385724
DOIs
StatePublished - 2024
Event9th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2024 - Tokyo, Japan
Duration: 8 Jul 202410 Jul 2024

Publication series

NameICARM 2024 - 2024 9th IEEE International Conference on Advanced Robotics and Mechatronics

Conference

Conference9th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2024
Country/TerritoryJapan
CityTokyo
Period8/07/2410/07/24

Fingerprint

Dive into the research topics of 'Hybrid Algorithm Research Based on Improved Genetic Algorithm and Auction Algorithm for AUVs Task Allocation'. Together they form a unique fingerprint.

Cite this