Whale Optimization Algorithm and Its Improvements

WOA is a bionic swarm algorithm, which overcomes the challenge of traditional algorithms. In practical application, WOA still has some problems, such as low convergence accuracy, slow optimization speed, and easy to fall into local optimal. On the basis of combing and analyzing the research status at home and abroad, firstly, the basic WOA is studied, including the mathematical models of surround prey, catch prey and hunt for prey, provide guidance for computer programming. Then, the basic WOA is analyzed, including strength analysis and weakness analysis. Then, the improved whale optimization algorithm is studied, and the improved scheme is proposed from two aspects of convergence factor and adaptive weight, which is easier to jump out of the local optimal value and effectively avoid the occurrence of premature convergence. Finally, the simulation experiment is carried out, the experimental environment and parameters are designed, and the results are analyzed, which proves that IWOA is better than WOA.