Improved Carnivorous Plant Algorithm based on Hybrid Strategy and its application
Yipeng Ji, Haotian Yang, Zhixin Sun · 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) · 2022
An improved Carnivorous plant algorithm (ICPA) based on a hybrid strategy method was proposed. By introducing an elite opposition-based learning strategy, the problem of population quality reduction of the basic carnivorous plant algorithm was solved. The quadratic interpolation method is helpful to improve the convergence rate. The disturbance through the Levy-flight strategy is beneficial to jump out of the local optimum. In each iteration, the adaptive weight factor determines whether to carry out reverse learning and quadratic interpolation, which balances the global and local search capabilities of the carnivorous plant algorithm. A set of benchmark test functions and the simulation results of wireless sensor network coverage optimization show that ICPA has good robustness, optimization accuracy, and optimization speed in solving the optimal value problem.