Application of an improved Discrete Salp Swarm Algorithm to the wireless rechargeable sensor network problem - Yi, Zhang; Yangkun, Zhou; Hongda, Yu; Hong, Wang (Frontiers in Bioengineering and Biotechnology, 2022)
This paper presents an improved Discrete Salp Swarm Algorithm based on the Ant Colony System (DSSACS). Firstly, we use the Ant Colony System (ACS) to optimize the initialization of the salp colony and discretize the algorithm, then use the crossover operator and mutation operator to simulate the foraging behavior of the followers in the salp colony. We tested DSSACS with several algorithms on the TSP dataset. The experiments show that our algorithm has a faster convergence speed, better positive feedback mechanism, and higher accuracy. We also apply the new algorithm for the Wireless rechargeable sensor network (WRSN) problem. Results show that DSSACS has a faster convergence speed and better positive feedback mechanism in MCV’s multi-path planning and saves more time and economic cost than other swarm intelligence algorithms in the wireless rechargeable sensor network.