Multi-beam Sounding Line Optimization Algorithm based on Genetic Algorithm and Greedy Algorithm

This paper primarily investigates the optimization of survey lines in multibeam bathymetric systems under varying seabed conditions. By integrating genetic algorithms and greedy algorithms, we optimize the configuration of survey line distances to maximize the efficiency and accuracy of seabed depth measurements. A cross-sectional model of survey lines and seawater depth is established, determining the depth and coverage width for several survey lines at different distances from the central point. A cross-sectional model perpendicular to the survey lines is constructed, and through geometric relationships, a mathematical model between multibeam bathymetry and survey line coverage width is developed. This model ultimately reveals the relationship between various survey line directions and seawater depth. When dealing with real seabed data, the survey line scheme needs to be as simple as possible. The evaluation criterion is the shortest total length of survey lines while covering the entire surveyed area. The constraints include ensuring an overlap rate between adjacent survey lines of 10% to 20% and minimizing the total length of the survey lines. The goal is to achieve comprehensive coverage of the entire sea area. This paper proposes a route optimization algorithm based on an improved genetic algorithm combined with a greedy algorithm. Iterative operations are performed through the route optimization algorithm, ultimately yielding a theoretically optimal set of survey lines.