A multi-objective robust optimization scheme for reducing optimization performance deterioration caused by fluctuation of decision parameters in chemical processes

作者：Liao Zhiqiang^*; Li Taifu; Chen Peng; Zuo Shilun

来源：Computers & Chemical Engineering, 2018, 119: 1-12.

DOI：10.1016/j.compchemeng.2018.08.037

• Decision parameters fluctuation
• Robustness evaluation metric
• Chemical process
• Multi-objective robust optimization

The fluctuation of decision parameters will deviate from the optimal decision, which will have significant impact on the optimization performance of chemical processes. To reduce optimization performance deterioration caused by fluctuation of decision parameters in chemical processes, a multi-objective robust optimization scheme is developed to assess performance robustness. In addition, based on the model that maps decision parameters to objective performance through neural network, a new robustness evaluation metric is created as the fitness value of the multi-objective evolutionary algorithm (for improving the strength Pareto evolutionary algorithm (SPEAII)) to elaborate the relationship between robustness and fluctuation. The efficacy of the proposed method is verified with HCN production process application by comparing with genetic algorithm (GA) and weighted single-objective robust optimization.

• 出版日期2018-11-2
• 单位重庆科技学院