###### Abstract  
This study focuses on optimizing the foundation pit dewatering scheme using the foundation pit dewatering theory and the principles of multi-objective optimization. It explores the development of a multi-objective optimization model and efficient solution technology for foundation pit dewatering. This research focuses on the foundation pit dewatering project at the inverted siphon section of Xixiayuan canal head, specifically from pile number XZ0+326 to XZ0+500. It establishes an optimized mathematical model for foundation pit dewatering that incorporates three objectives. Additionally, a dewatering optimization program is developed by utilizing the MATLAB optimization toolbox and the multi-objective optimization algorithm program based on the NSGA-II algorithm (Gamultiobj). The multi-objective optimization mathematical model is solved, and a Pareto-optimal solution set with uniform distribution is obtained. The multi-objective optimization evaluation system based on AHP is constructed from the three aspects of dewatering cost, the impact of settlement on the environment, and the safety and stability of the foundation pit. The optimization scheme of the Pareto-optimal solution set is selected as the decision result to provide multiple feasible schemes for the dewatering construction of foundation pits. The optimization scheme is verified by using the GMS software. The simulation results demonstrate that the optimization scheme fulfills the requirements for water level and settlement control. Moreover, the developed optimization program efficiently solves the multi-objective optimization problem associated with foundation pit dewatering. Lastly, an evaluation system incorporating the NSGA-II algorithm and AHP is developed and utilized in the context of dewatering engineering in order to offer multiple viable optimal dewatering schemes. multi-objective optimization; NSGA-II algorithm; Pareto-optimal solution set; evaluation system; foundation pit dewatering Article Research on Multi-Objective Optimization Model of Foundation Pit Dewatering Based on NSGA-II Algorithm Applied Science  
[PERSON], [PERSON], [PERSON], Y. In recent years, significant progress has been made in the research and application of optimization algorithms at home and abroad. The genetic algorithm, simulated annealing, the Ant colony algorithm, and particle swarm optimization have made important breakthroughs in theoretical research and practical application [1]. The utilization of optimization algorithms is crucial in enhancing efficiency, reducing costs, and optimizing resource utilization. [PERSON] introduced a variety of multi-objective optimization algorithms to optimize the power generation efficiency of the hydropower station reservoir [2]. [PERSON] applied the NSGA-II algorithm to power grid optimization planning, established the design model of multi-objective power grid planning, and provided schemes for the trade-off analysis of various objectives. Based on the objective function method [3], [PERSON] optimized and analyzed the dewatering plan for a subway foundation pit with the minimum total water inflow as the objective function and combined with the water level constraints of each control point [4]. [PERSON] applied the genetic algorithm to determine the optimal number of wells for foundation pit dewatering and used a simple and efficient genetic algorithm to control a set of model sets to obtain the overall optimal plan [5]. [PERSON] proposed a NPTSGA algorithm, which combines the genetic algorithm and the tabu search algorithm. The algorithm was used to simulate and optimize the problem of seawater intrusion in coastal areas [6]. [PERSON] incorporated the crossover operator of the genetic algorithm into the position change phase of the firefly algorithm, and fused the two algorithms to solve the optimization problem [7].