To solve the problems of difficult decision-making, multiple interference factors, poor real-time performance and the realization of global optimization in maritime search and rescue (SAR) resource scheduling, this study employs an improved non-dominated sorting genetic (NSGA-II) algorithm by taking the Yellow Sea and the Bohai Sea as an example. Firstly, a multi-objective optimization model for maritime SAR resources is built based on AIS and BeiDou data. Secondly, the normal distribution crossover (NDX)-based operator is adopted by the improved NSGA-II algorithm to avoid falling into local optimum on the basis of expanding the search scope, and a complete Pareto solution set for the multi-objective problem is obtained. The comprehensive evaluation method (TOPSIS) is applied to obtain a compromise solution from the Pareto solution set, namely the optimal design of the search and rescue scheduling scheme. Finally, when the constraint factors such as the number of ships and time are considered, the improved NSGA-II algorithm is employed and compared with the NSGA-II and greedy algorithms. The simulations of the resource scheduling are carried out using the data collected from ships in the Yellow Sea and the Bohai Sea. The results show that the algorithm can effectively solve the problem of maritime SAR resource scheduling optimization.