The Application of an Improved PSO Based on the Quantum Genetic Algorithm in the Submersible Path-Planning

Abstract

An improved particle swarm optimization algorithm (PSO) combined with quantum genetic algorithm is proposed, to solve the problems that the PSO is difficult to converge for benchmark complex problems and it's parameters are hard to define. The new algorithm is used for submersible path planning and simulation on some standard test functions. The results show that the improved is superior to the standard PSO in optimization ability and the convergence rate, and it can find the optimal path faster.