An active set truncated-Newton algorithm (ASTNA) is proposed to solve the large-scale bound constrained sub-problems. The global convergence of the algorithm is obtained and two groups of numerical experiments are mad...An active set truncated-Newton algorithm (ASTNA) is proposed to solve the large-scale bound constrained sub-problems. The global convergence of the algorithm is obtained and two groups of numerical experiments are made for the various large-scale problems of varying size. The comparison results between ASTNA and the subspace limited memory quasi-Newton algorithm and between the modified augmented Lagrange multiplier methods combined with ASTNA and the modified barrier function method show the stability and effectiveness of ASTNA for simultaneous optimization of distillation column.展开更多
Reduced-space SQP algorithms for optimization of distillation column are studied.Variables decomposition is used to eliminate dependent variables and equality constraints,which reduce the dimension of QP sub-problems ...Reduced-space SQP algorithms for optimization of distillation column are studied.Variables decomposition is used to eliminate dependent variables and equality constraints,which reduce the dimension of QP sub-problems involved in iterations of SQP.Compared with the one based on orthonormal bases,reduced-space SQP based on orthogonal bases retains the convergence property while avoids QR decompositon.The improved computation efficiency is illustrated in a enzene/toluene distillation column optimization example, based on author’s,previous work.展开更多
基金Project (2002CB312200) supported by the National Key Basic Research and Development Program of China Project(03JJY3109) supported by the Natural Science Foundation of Hunan Province
文摘An active set truncated-Newton algorithm (ASTNA) is proposed to solve the large-scale bound constrained sub-problems. The global convergence of the algorithm is obtained and two groups of numerical experiments are made for the various large-scale problems of varying size. The comparison results between ASTNA and the subspace limited memory quasi-Newton algorithm and between the modified augmented Lagrange multiplier methods combined with ASTNA and the modified barrier function method show the stability and effectiveness of ASTNA for simultaneous optimization of distillation column.
文摘Reduced-space SQP algorithms for optimization of distillation column are studied.Variables decomposition is used to eliminate dependent variables and equality constraints,which reduce the dimension of QP sub-problems involved in iterations of SQP.Compared with the one based on orthonormal bases,reduced-space SQP based on orthogonal bases retains the convergence property while avoids QR decompositon.The improved computation efficiency is illustrated in a enzene/toluene distillation column optimization example, based on author’s,previous work.
