2. Encapsulation group optimization algorithm

The Tunicate Swarm Algorithm (TSA) is a new optimization Algorithm proposed by Satnam Kaur et al. It is inspired by the Swarm behavior of the successful survival of the coating in the deep sea. The Algorithm can simulate the jet propulsion and Swarm behavior of the encapsulated animals during navigation and foraging. Compared with other competitive algorithms, TSA algorithm can produce better optimal solutions and solve real case studies with unknown search space.

2. Simulation results

Suppose the monitoring area is a two-dimensional plane of 50m×50m ×50 M50m ×50m, the number of sensor nodes N=35N= 35N=35, and the sensing radius is R S =5m R_s =5 mRs=5m. Communication radius R C =10m R_c= 10 mRc=10m, 300 iterations. The evolution curves of initial deployment, TSA optimal coverage, and TSA algorithm coverage are shown in Figure 1-3.

Figure 1 Initial deployment

Figure 2. TSA optimized coverage

FIG. 3 Evolution curve of TSA coverage

[1] Song Tingting, ZHANG Damin, Wang Yiru, et al. [2] Kaur S, Awasthi L K, Sangal A L, et al. Optimization of WSN coverage based on improved whale optimization algorithm [J]. Chinese Journal of Sensors and Actuators, 2020, 033(003):415-422. et al. Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization[J]. Engineering Applications of Artificial Intelligence, 2020, 90 (Apr) : 103541.1 to 103541.29.

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