A new method is presented for the optimal design of distillation columns with structural and operational decisions. This has been a challenging issue because of difficulties such as complexity of problem formulation, numerical instabilities and lengthy computational times. The new approach presented here solves combinatorial optimization problems by a pattern search method. In the method, the best combination of integer values, each representing the number of stages placed in a column section of a distillation unit, is identified by comparing the objective values evaluated by the embedded NLP solver, while derivatives are not used explicitly. The reliability of the implemented algorithm is numerically confirmed by solving DWC (dividing wall column) problems. This reliability is due to the use of globally convergent pattern search in combination with a full-space Hessian SQP algorithm where global convergence in large and highly nonlinear flowsheeting problems is ensured (Ishii & Otto, 2018).

提出了一种新的方法，可根据结构和操作决策优化蒸馏塔的设计。由于诸如问题制定的复杂性，数值不稳定性和冗长的计算时间之类的困难，这一直是一个具有挑战性的问题。这里提出的新方法通过模式搜索方法解决了组合优化问题。在该方法中，整数值的最佳组合是通过比较嵌入式NLP求解器评估的目标值来确定的，每个整数代表放置在蒸馏单元塔段中的级数，而没有明确使用导数。通过解决DWC（分隔壁柱）问题，可以从数字上确认所实现算法的可靠性。