Improved Sequential Least Squares Programming–Driven Feasible Path Algorithm for Process Optimisation - Ma, Yingjie; Zhang, Nan; Li, Jie (Computer Aided Chemical Engineering, 2022)
Sequential least squares programming (SLSQP) algorithm has been shown to be useful for driving the feasible path algorithms for process optimisation. However, the existing SLSQP algorithms still need many function evaluations for computationally challenging process optimisation problems. In the current work, we propose several novel strategies to improve both the efficiency and convergence of the SLSQP algorithm. Solving a large-scale process optimisation problem indicates that the algorithm can save computational times by 10-90% with better solutions generated.