非线性污水处理过程的多目标优化

Multi-objective optimization of nonlinear wastewater treatment process

研究了复杂非线性污水处理过程的多目标优化。针对污水处理过程的非线性动力系统,建立了使污水处理过程运行成本和描述实际输出与期望输出偏差的平方可积误差设计指标同时达到最优的多目标优化模型。采用间接优化方法,首先将描述污水处理过程优化的多目标非线性问题转化为多目标线性规划问题,然后利用遗传算法对其进行求解。本文方法不仅获得了多目标优化问题的近似Pareto前沿,而且由于采用的是多目标线性规划方法,所以具有计算成本低的优点。

Multi-objective optimization of wastewater treatment process was studied. According to a nonlinear dynamic model of wastewater treatment process, a multi-objective optimization model was established. The economic cost and integral square error between actual and desired outputs were optimized simultaneously to perform a wastewater treatment plant. The original multi-objective nonlinear problem describing the process optimization of a wastewater treatment plant was first transformed into a multi- objective linear programming by using the indirect optimization method （IOM）. A powerful multi- objective optimization genetic algorithm was used to derive the Pareto optimal solutions, which could illustrate the whole trade-off relationships between objectives. The approach proposed not only obtained the approximate Pareto fronts of multi-objective optimization problem, but also had a low computational burden due to the use of multi-objective linear programming method.