The multi-objective optimization of methanol distillation is a critical and complex issue in the methanol industry. The three-column methanol distillation scheme is first simulated with Aspen Plus to provide the initial value of the NSGA-III algorithm. The operating parameters are optimized through the Python-Aspen platform. The total annual cost and CO₂ emissions are considered the objective function. A small value of indicator generational distance can be achieved by increasing the number of generations, which is helpful in improving algorithm convergence. The NSGA-III algorithm has good convergence and distribution performance. By comparing the optimized results with the original ones, the total annual cost and CO₂ emissions are, respectively, reduced by 5.35% and 12.80% when the operating parameters of the methanol distillation sequence are optimized through NSGA-III. As a result, substantial economic and energy savings can be made, offering great potential to improve the performance of the three-column methanol distillation.

Optimal synthesis of distillation sequence is a complex problem in chemical processes engineering, which involves process structure optimization and operation parameters optimization. The study of the synthesis of distillation sequence is a crucial step toward improving the efficiency of chemical processes and reducing greenhouse gas emissions. This work introduced the concept of binary tree to encode the distillation sequence. The performance of the six evolutionary algorithms was evaluated by solving a 14-component distillation sequence synthesis problem. The best algorithm was used to optimize the operation parameters of a triple-column distillation process. The total annual cost and CO₂ emissions were considered as the metrics to evaluate the performance of triple-column distillation processes. As a result, NSGA-II-DE was found to be the best one of the six tested evolutionary algorithms. Then, NSGA-II-DE was applied to the distillation sequence optimization to find the best operating parameters, which led to a significant reduction in CO₂ emission and total annual costs.