针对加压输水与重力输水相结合的长距离复杂输水工程利用单阀调控难以改善全线水锤控制效果的问题，该文建立了耦合水力计算的泵阀联合优化调控模型，应用了基于非支配排序的多目标浣熊优化算法(NSCOA)求解，并通过改进理想点法(IIPBD)对计算生成的Pareto前沿解进行方案优选。以山东省某加压输水与重力输水相结合的输水工程为例，分别采用NSCOA、NSGA-Ⅱ、NSSA对其泵阀联合优化调控模型进行求解，通过超体积指标(HV)、间距指标(SP)进行评价，验证了NSCOA在泵阀联合调控问题中寻优性能的优越性。结果表明，利用IIPBD优选的方案比现状方案的最大水锤压力降低了15.28 m，最小水锤压力降低了0.03 m，高位水池水位波动幅度减小了70.37%。研究成果可为解决实际工程中的泵阀联合优化调控提供参考。

Objective: For long-distance and complex water conveyance systems that combine pressurized water and gravity flow, achieving effective water hammer control through individual valve regulation is challenging. It is crucial to implement joint pump-and-valve operation to ensure the system's overall safety performance. Existing research often overlooks water level fluctuations in storage facilities and fails to evaluate the effects of coordinated pump-and-valve operations on the overall system. Furthermore, the interdependence of parameters in multivariable pump-and-valve control creates difficulties in multi-objective optimization and decision-making. Methods: The joint optimal operation model for pumps and valves is developed based on hydraulic calculations, considering three key objectives: minimizing the maximum water hammer pressure, maximizing the minimum water hammer pressure, and minimizing water level fluctuations in elevated pools. The model is solved using the non-dominated sorting-based multi-objective coati optimization algorithm (NSCOA), while optimization schemes are realized through improved ideal-point-based decision (IIPBD) derived from the computationally generated Pareto front. A long-distance water transmission project serves as the research object, where NSCOA, NSGA-Ⅱ, and NSSA are used to solve its joint optimal pump-and-valve operation. Reasonable parameter settings for NSCOA are determined to solve the model. The optimal solution is obtained using IIPBD, validating the superiority of the NSCOA-IIPBD optimization decision-making method. Results: The performance of NSCOA, NSGA-Ⅱ, and NSSA was evaluated using hypervolume (HV) and spacing (SP) indices across ZDT1 to ZDT4 and ZDT6 test functions, confirming the superiority of NSCOA. At the same time, the parameters of NSCOA in the calculation of joint optimal operation of pumps and valves are reasonably set: the population number is 50, the size of external archives is 50, and the number of iterations is 75. Comparisons with NSGA-Ⅱ and NSSA further demonstrated the effectiveness of NSCOA in solving this problem. On this basis, the Pareto frontier calculated by NSCOA is determined based on IIPBD. Compared with the current scheme, the optimal scheme shortened the fast-closing time, extended the slow-closing time of the valve after the pump, and coordinated pump time intervals with the terminal valve response. These adjustments resulted in a 14.40% reduction in maximum pressure and a 70.37% decrease in water level fluctuation in the elevated pool. These findings confirm the reliability of NSCOA for optimizing the joint optimal operation model of pumps and valves under phased shutdown of pumps. Conclusions: The widely distributed Pareto frontier solution set can be obtained by solving the joint optimal operation model of pumps and valves with NSCOA. Using IIPBD, an optimal scheme with significantly lower pressure and water level fluctuations compared to the current scheme was achieved. The NSCOA-IIPBD method provides a more efficient and feasible scheme for the multi-objective solution and decision-making of the joint optimal operation of pumps and valves in long-distance complex water transmission systems.