Abstract
Trust allocation (TA) is an important part in dynamic positioning system. The function of TA is to allocate thrust and angle of each thruster so that the desired force and moment can be achieved. In this study, a hybrid artificial bee colony algorithm with chaotic search (HABCC) which introduces mutation operator from differential evolution (DE), social cognitive part from particle swarm optimisation (PSO) to honeybee search strategy and chaotic search to scouts searching, is proposed. Therefore, the capacity of exploration and exploitation is greatly improved. The optimal search of HABCC is speeded up compared with traditional ABC algorithm and the probability of finding the optimal results and avoiding local optimum is significantly increased. The effectiveness of the HABCC algorithm is demonstrated by simulations.
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