Calculated weights by traditional PCM (pairwise comparison matrix) adjustment methods can't retain the information of the original PCM to the maximum extent. Therefore, a method for PCM modulation based on the weights was proposed. The method constructed a completely consistent matrix according to the properties of weights, and the matrix was fitted by the AdaGrad method, so as to minimize the total change of the matrix relative to the original PCM. Corresponding weights was taken as the calculation result of the matrix. Numerical results show that this method can significantly improve the retention of original PCM information compared with other methods and does not require repeated consistency checking.

Aiming at the problem of poor applicability of current path planning results for underwater vehicles, a three-dimensional path planning algorithm for underwater vehicles based on improved particle swarm optimization algorithm was proposed. A Voronoi map based on the real terrain data of sea area was built, and the Dijkstra algorithm was used to generate the initial path set that meets the requirements of navigation safety as the initial particles of particle swarm optimization algorithm, so the generation efficiency of initial particles was improved. At the same time, the particles′ position update method was improved to guide the particle position change according to the position of adjacent nodes on the route, which makes the planned route smoother and more suitable for the navigation of underwater vehicles. Simulation results show that the proposed algorithm is more robust and has better applicability than the traditional particle swarm optimization algorithm in path planning.