Genetic Algorithm Solution of a Gray Nonlinear Water Environment Management Model Developed for the Liming River in Daqing, China

Abstract

This paper presents the genetic algorithm (GA) solution of a gray nonlinear water environment management model we developed for the Liming River basin in Daqing, China to improve the water environment management. The model has been developed by both optimizing the operation of wastewater treatment plants and making full use of assimilative capacity of the river so that the optimum integration of these two measures can keep the water quality in the Liming River basin up to a satisfactory standard at a reasonable cost. It can be used as an example to illustrate the potential application of a GA-based gray nonlinear programming in the field of water environment management.