Abstract: Chemical process optimization can be described as large-scale nonlinear constrained
minimization. The modified augmented Lagrange multiplier methods (MALMM) for large-scale
nonlinear constrained minimization are studied in this paper. The Lagrange function
contains the penalty terms on equality and inequality constraints and the methods can be
applied to solve a series of bound constrained sub-problems instead of a series of
unconstrained sub-problems. The steps of the methods are examined in full detail. Numerical
experiments are made for a variety of problems, from small to very large-scale, which show
the stability and effectiveness of the methods in large-scale problems.

Key words: modified augmented Lagrange multiplier methods, chemical engineering optimization, large- scale non linear constrained minimization, numerical experiment

摘要： Chemical process optimization can be described as large-scale nonlinear constrained
minimization. The modified augmented Lagrange multiplier methods (MALMM) for large-scale
nonlinear constrained minimization are studied in this paper. The Lagrange function
contains the penalty terms on equality and inequality constraints and the methods can be
applied to solve a series of bound constrained sub-problems instead of a series of
unconstrained sub-problems. The steps of the methods are examined in full detail. Numerical
experiments are made for a variety of problems, from small to very large-scale, which show
the stability and effectiveness of the methods in large-scale problems.

关键词: modified augmented Lagrange multiplier methods;chemical engineering optimization;large- scale non linear constrained minimization;numerical experiment