Improved Sequential Least Squares Programming–Driven Feasible Path Algorithm for Process Optimisation

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 curr...

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Vydáno v:Computer Aided Chemical Engineering Ročník 51; s. 1279 - 1284
Hlavní autoři: Ma, Yingjie, Zhang, Nan, Li, Jie
Médium: Kapitola
Jazyk:angličtina
Vydáno: 2022
Témata:
feasible path
line search
numerical errors
process optimisation
SLSQP
process optimisation
feasible path
SLSQP
numerical errors
line search
ISBN:0323958796, 9780323958790
ISSN:1570-7946
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Shrnutí: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.
ISBN:0323958796
9780323958790
ISSN:1570-7946
DOI:10.1016/B978-0-323-95879-0.50214-9