Intelligent Optimal Control of Sewage Treatment Based on Multiobjective Evolutionary Algorithm

Abstract

In order to solve the problem of optimal control of the sewage treatment process based on a multiobjective evolutionary algorithm, an intelligent optimal control of sewage treatment based on a multiobjective evolutionary algorithm is proposed in this paper. In this paper, the decomposition based multiobjective evolutionary algorithm (MOEA/D) is improved, and it is expected that the uniformly distributed approximate Pareto frontier can be obtained with fewer evolution times. For each new solution generated by the MOEA/D algorithm, the improved algorithm in this paper finds the most suitable subproblem for the new solution from all subproblems and replaces the population in its neighborhood. On the basis of the original subproblem, it carries out secondary optimization to improve the utilization rate of the children and then finds the approximate Pareto frontier in the optimization problem with fewer iterations. The experimental results show that AE, PE, and EC Based on SS–MOEA/D optimal control method are reduced by 6.91%, 1.54%, and 5.58%, respectively. Conclusion. The algorithm significantly reduces the number of steps to find the Pareto frontier, significantly improves the performance of the MOEA/D algorithm, and achieves the optimization goal in the optimization of the sewage treatment process.

Retracted: Intelligent Optimal Control of Sewage Treatment Based on Multiobjective Evolutionary Algorithm

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