关键词: 特殊社会责任, 水环境治理, 项目群鲁棒性优化, 净现值优化, 优化NSGA-Ⅲ算法

Abstract: The report of the 20th National Congress of the Communist Party of China clearly pointed out that it was necessary to intensify the prevention and control of environmental pollution, make further efforts to keep waters clear, improve water resources, aquatic environments, and aquatic ecosystems, and strengthen ecological conservation of major rivers, lakes, and reservoirs. Improving the environmental governance of important rivers is vital to the great rejuvenation and sustainable development of the Chinese nation. The main body of aquatic environmental governance in China is generally state-owned enterprises, which generally are in the form of programs. Although the state-owned enterprises enjoy unique advantages in various policies and resources, the effect of aquatic environmental governance is still unsatisfactory. The fundamental reason is that there is more public welfare in aquatic environmental governance projects. It is necessary to rely on the governance enterprises to fulfill their special social responsibilities to achieve certain governance goals, which is contrary to the profit purpose of enterprises, coupled with various uncertain factors, resulting in low profitability of aquatic environmental governance projects. Therefore, it is necessary to establish a scheduling method from the perspective of enterprises, so as to fulfill certain special social responsibilities, increase their profitability and anti-risk ability, and ensure that the governance effect of water environmental governance programs meets the standards. This is of great significance to the benign development of governance enterprises and the implementation of water environmental governance strategy in China.
This paper derives the concept and connotation of special social responsibility of water environmental governance enterprises from the concept of social responsibility and the responsibilities undertaken by state-owned enterprises. It believes that there is a correlation between the fulfillment of special social responsibility and the effectiveness of water environmental governance, proposes a solution to the problem from the perspective of project portfolio and scheduling, and constructs a dual objective optimization model for the net present value and robustness of programs. In view of the difficulty of solving complex constraint problems using conventional algorithms, this paper puts forward a NSGA-III algorithm optimized by Multi Population Genetic Algorithm (MPGA), which transforms a single population into multiple populations in parallel, adds immigration operations in each iteration process, and can maximize the retention of key information in the population and avoid overfitting. In the algorithm, there are two layers of encoding structure. The first layer uses binary encoding to represent the proportion of special social responsibility fulfillment, while the second one represents the start time of different projects. In order to verify the effectiveness of the model and algorithm described in this paper, Program A is taken as an actual case study. The governance content is to renovate the overall water conservancy facilities in the entire city, with the governance goal of improving the water quality cross-section rate by 5% as the basic goal and 12.5% as the high standard goal.
The study reaches the following four conclusions: (1)In terms of algorithm advantages, the NSGA-III algorithm based on multi-population genetic algorithm optimization can adapt to complex constraints very well and find more Pareto solutions, which has greater advantages than Multi-Objective Particle Swarm Optimization (MOPSO), standard NSGA-III algorithm, and Multi-Objective Grey Wolf Optimizer algorithm (MOGWO). (2)The net present value and robustness of the program approximately show a negative correlation relationship, that is, the higher the program’s net present value, the weaker its robustness; conversely, the lower the program’s net present value, the stronger its robustness. (3)The robustness of the program scheduling scheme is resistant to uncertain environments, that is, the stronger the robustness of the program, the less adverse impact it will suffer. At the same time, the scheduling scheme with high net present value robustness is more compact, while the more relaxed scheduling scheme will bring greater net present value, which is contrary to the conventional cognition. (4)The government’s subsidies or rewards for water environmental governance enterprises are crucial and conducive to improving the effect of water environmental governance. If the government does not give rewards, the enterprises may suffer losses, which will damage their enthusiasm in the long run and cause counterproductive effects.
This paper explains the special social responsibility of water environmental governance enterprises, takes full account of the coordination of water environmental governance effect and enterprise profitability, and provides a new scheduling method for enterprises and some ideas for the government to formulate a reward and punishment system. Future studies will be devoted to further exploring the correlation of multiple objectives such as robustness, qualitative robustness, net present value, and governance effect of the scheduling solution, and developing a more suitable and efficient algorithm.

Key words: special social responsibility, water environmental governance, program robust optimization, net present value optimization, optimized NSGA-Ⅲ algorithm