CIESC Journal ›› 2006, Vol. 57 ›› Issue (3): 614-619.
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YUE Jincai;YANG Xia;ZHENG Shiqing;HAN Fangyu
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岳金彩;杨霞;郑世清;韩方煜
Abstract: Sequential Quadratic Programming (SQP) is the most efficient algorithm for nonlinear optimization.But a penalty function is usually used for linear search,causing some problems.Filter-SQP developed by Roger Fletcher and Sven Leyffer avoids using penalty function.In the view of filter-SQP, NLP problem has two objectives, one is minimizing objective function, the other is satisfying the constraints.The concept of filter is proposed on the basis of these two objectives.In this paper flowsheet optimization using filter-SQP in modular simulator environment was studied.Infeasible path strategy was used and the constraint function was composed of tear stream equation, specific design and unsatisfied inequality constraint.When filter could not find a step as the starting point of the next iteration, in order to avoid algorithm failure three strategies were used.They were restarting strategy, converging recycle strategy and feasible path strategy.A successive scaling strategy was proposed for filter-SQP to improve the efficiency of optimization.A case study of process optimization with filter-SQP was very encouraging.
Key words: 模块环境, 过程优化, filter-SQP, 规格化
关键词: 模块环境, 过程优化, filter-SQP, 规格化
YUE Jincai, YANG Xia, ZHENG Shiqing, HAN Fangyu. Filter-SQP in modular simulator environment for process optimization[J]. CIESC Journal, 2006, 57(3): 614-619.
岳金彩, 杨霞, 郑世清, 韩方煜. 模块环境下的filter-SQP用于过程优化 [J]. 化工学报, 2006, 57(3): 614-619.
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https://hgxb.cip.com.cn/EN/Y2006/V57/I3/614
HONG Weirong;WANG Yan;TAN Pengcheng
Chemical process optimization approach based on primal-dual interior-point method