Reservoir flood control has an important impact on flood protection and plays an important role in reducing the loss of people’s lives and property. In order to play an important role in flood control operation of large-scale reservoirs, a control flood dispatching multi-objective evolutionary algorithm based on decomposition (CFD-MOEA/D) is proposed. The same type of multi-objective optimization algorithm (non-dominated sorting genetic algorithm II (NSGA-II)) is introduced, and CFD-MOEA/D, NSGA-II, and traditional MOEA/D algorithms are compared. The research results show that the CFD-MOEA/D algorithm can obtain the non-dominated solution of the higher water level in the upstream, and the solution obtained by the CFD-MOEA/D algorithm is more sufficient than the NSGA-II algorithm and the MOEA/D algorithm. When analyzing the HV value curve, the uniformity and convergence of the optimal solution obtained by the CFD-MOEA/D algorithm are better than those of the other two algorithms. The optimal dispatching scheme of the CFD-MOEA/D algorithm is compared with the actual dispatching scheme of the reservoir, and it is found that the maximum upstream water level and the final water level obtained by the CFD-MOEA/D algorithm are both kept at approximately 325 m, which is consistent with the actual dispatching scheme. The new feature of the algorithm is that it uses a decomposition method from coarse to fine and improves the hourly scheduling scheme to obtain higher scheduling efficiency.

In the past, the optimization of engineering specifications primarily included the influence of quality loss terms on product quality; however, in actual production practice, compensation quantity inevitably affects the optimization quality of engineering specifications. In this paper, the quadratic exponential quality loss and gain function was first supplemented, and the quadratic exponential quality loss and gain function was constructed under the larger-the-better characteristic and the smaller-the-better characteristic; in order to accurately represent the change in compensation amount in the process of quality control, the optimization method of engineering specification under the calculation of quality loss and compensation was given in combination with the hyperbolic tangent function. Finally, with the support of the dam construction quality acceptance assessment, the engineering specification optimization model was tested. The optimal coefficient was obtained as 0.162, and the specification range was reduced from 0.744 to 0.648, achieving the optimization goal.

On the basis of analyzing the relationship between a contractor’s credit, project quality assurance, owner’s monitoring level, and the quality guarantee deposit, the quality expected benefit model of the owner and the contractor was constructed under the conditions of symmetric information and asymmetric information, in which the owner assumed the primary responsibility for the project quality, the project characteristics were incorporated, the credit level was taken as the contractor’s decision variable, and the project quality monitoring level and detention of the quality guarantee deposit were taken as the owner’s decision variables. In light of the maximum value principle, an optimal solution to the owner’s quality monitoring decision and the quality deposit detention strategy was derived; through the simulation calculation, the decision-making results under different information conditions were analyzed.

The Journal retracts the article titled “Application Research of CFD-MOEA/D Optimization Algorithm in Large-scale Reservoir Flood Control Scheduling”