A method to circumvent the combinatorial difficulties in the optimal design of distillation columns

摘要

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).