Data for Path Planning of a Coupled AUVs System for Adaptive Sampling

We studied a path planning problem of a coupled AUVs system for adaptive sampling. This type of system consists of a main AUV and multiple small AUVs that can be carried by it. Small AUVs can be launched by the main AUV and require recovery. This paper provides a mixed integer linear programming (MILP) model aimed at optimal routing and scheduling of the coupled AUVs system which satisfies time window constraints and collaborative constraints between multiple AUVs. On this basis, a matheuristic algorithm is designed to quickly approximate the optimal solutions for problems with practical size. The core of this algorithm is the combination of mathematical programming as a local search method and variable neighborhood search (VNS) strategy. The ocean field map used is the uncertainty field in the surface temperature forecasts about hycom_glb_regp01_2023102900_t003.nc which was obtained from the National Oceanic and Atmospheric Administration (NOAA). The experimental results show that the proposed matheuristic algorithm can be effective in improving the sampling efficiency and data quality of the coupled AUVs system. Due to the author using a computer from ten years ago for computing, the algorithm performance has been affected. Hope to receive funding support as soon as possible.