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.
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