Behaviour-based grey wolf optimiser for a wireless sensor network deployment problem. (14th February 2022) - Qiao, Yu; Hsu, Hung-Yao; Pan, Jeng-Shyang
The existing grey wolf optimiser does not perform well in convergence and diversity of the population. This paper investigates the grey wolf optimiser and proposes a behaviour-based grey wolf optimiser (BGWO) based on the real behaviours of the wolf pack. In BGWO, it mainly consists of two strategies: The lost wolf strategy and the mating strategy. BGWO increases the population diversity of wolves so that it is not easy to fall into a local optimum. Eighteen benchmark functions in CEC2017 are used to test the performance of BGWO and the result shows that the performance of BGWO is better than existing algorithms in the literature such as GWO, PSO, FA, and PSOGWO. Moreover, In the WSN problem, a combination of coverage rate, connectivity rate, and the total network energy consumption is proposed as the objective function and optimised by BGWO. The experimental results show that BGWO performs well than other algorithms.