At present, with the acceleration of industrialization and urbanization, the pollution of water resources is becoming increasingly prominent. Water resources are seriously polluted, which would cause the degradation of water body function, or even lose its function. This would not only lead to serious water shortage in areas with less water, but also lead to "water quality" water shortage in areas with more water. Water pollution (WP) has become the most prominent problem in the current water environment. In the face of this situation, this paper studies the prevention and control planning of WP, and puts forward the suggestion of applying genetic algorithm to the prevention and control planning of WP. The research shows that under the condition that the water quality is not polluted, genetic algorithm (GA) can save the cost of prevention and control planning more than particle swarm optimization in WP prevention and control planning, and can save 77 million yuan, 584.4 million yuan and 2565 million yuan in S, T and R regions respectively. At the same time, compared with particle swarm optimization algorithm, most respondents believe that GA has the characteristics of high efficiency and strong practicability.

Ulrich Mescheder. Fusion Genetic Algorithm in Water Pollution Prevention and Control Planning. Water Pollution Prevention and Control Project (2021), Vol. 2, Issue 2: 1-11. https://doi.org/10.38007/WPPCP.2021.020201.

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