Title: A formation generation algorithm of multiple agents in naval battlefield environments

Authors: Yani Cui; Jia Ren; Delong Fu; Chao Dong

Addresses: College of Information Science and Technology, Hainan University, Haikou 570228, China; Key Laboratory of Technology and Application for Safeguarding of Marine Rights and Interests, Guangzhou 510310, China ' College of Information Science and Technology, Hainan University, Haikou 570228, China ' College of Meterology and Oceanography, National University of Defense Technology, Changsha 410073, China ' Key Laboratory of Technology and Application for Safeguarding of Marine Rights and Interests, South China Sea Marine Survey and Technology Center, Guangzhou 510310, China

Abstract: This study aims to present a model of the formation generation for multiple agents using a modified binary particle swarm optimisation (MBPSO). The major objective of this study is to maximise the formation combat capability and reduce the formation generation cost. We treat the ratio of the aforementioned two values as a measure of formation combat effectiveness. Additionally, chaos theory is adopted in the initialisation of MBPSO to acquire diversified particle population. Moreover, particle diversity is utilised to dynamically adjust the particle position updating process to guarantee the global convergence. A case study for multi-agent formation generation model in a naval battlefield is conducted. It is shown that the proposed algorithm can accomplish multi-agent formation generation under multiple constraints. Compared with the existing related algorithms, the proposed algorithm has improved search performance and better convergence characteristics.

Keywords: multiple agents; formation generation; particle swarm optimisation; PSO; chaos theory; particle diversity.

DOI: 10.1504/IJSN.2019.098916

International Journal of Security and Networks, 2019 Vol.14 No.1, pp.34 - 46

Received: 23 Oct 2018
Accepted: 23 Oct 2018
Published online: 09 Apr 2019 *

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