Improved Genetic Algorithm for UUV Path Planning Based on Differential Evolution Algorithm
Aiming at the global path planning problem of underwater unmanned vehicles in a three-dimensional environment,the genetic algorithm was improved from the perspective of optimizing the initial population and improving convergence accuracy to find the optimal path.The fusion of genetic algorithm and differential evolution algorithm was studied.Using elite reverse learning to screen the initial population,finding the optimal initial population and integrating the idea of differential evolution algorithm to improve the genetic algorithm,enhancing the algorithm's global search ability.The results show that the improved algorithm has a faster initial convergence speed,and the planned curve can reduce UUV energy consumption,which to some extent improves the situation of getting stuck in local optimal solutions.
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