Application of many-objective particle swarm algorithm based on fitness allocation in WSN coverage optimisation Online publication date: Tue, 15-Jun-2021
by Weiwei Yu; Chengwang Xie
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 20, No. 3, 2021
Abstract: In order to improve the situation that the Wireless Sensor Network (WSN) nodes in the random deployment are not uniform and improve the network coverage performance, many-objective Particle Swarm Algorithm based on Fitness Allocation (FAMPSO) is proposed. The algorithm combines the fuzzy information theory to associate the Ideal Solution (IS) with the Pareto Solution (PS) and proposes a new fitness allocation method, which increases the pressure of population selection and enhances the convergence of the algorithm. The FAMPSO algorithm is compared with three other representative multi-objective evolution algorithms on the DTLZ series test function set. At the same time, the FAMPSO algorithm was applied to the coverage optimisation of WSN, and the simulation analysis was carried out. The simulation results show that the FAMPSO algorithm has a significant performance advantage in terms of convergence, diversity and robustness. FAMPSO algorithm improves the coverage performance of WSN.
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