Improved Nutcracker Algorithm based on Hybrid Strategy and Its Application in Wireless Sensor Network Coverage

To overcome the issues of reduced population diversity, susceptibility to local optima, and premature convergence in the Nutcracker Optimizer Algorithm (NOA), this paper proposes a multi-strategy improved Nutcracker Optimization Algorithm (INOA). aim at the problem of reduced population diversity during the iteration process, the Tent chaotic mapping is utilized to initialize the population, enhancing the richness and quality of the population throughout the optimization process. oriented algorithms are prone to local optimal problems, the tangent flight is employed instead of the original Levy flight, further harmonizing the algorithm's local exploitation and global search capabilities, thus enhancing its convergence ability. Simulation results on the CEC2005 benchmark test functions demonstrate that INOA exhibits superior optimization capability and stability. In the coverage optimization problem of wireless sensor network, experiments show that INOA improves coverage rates by 3.37% compared to NOA, thereby proving its effectiveness in addressing network coverage optimization problems.