大规模过程系统优化方法

The Optimization Method of Large-scale Process Systems

基于非线性约束的序列界无约束极小化方法,对大规模过程系统稳态优化的序列界约束极小化方法(SBCMM)进行了研究.对工程模型引进松弛变量处理后,SBCMM的罚函数仅包含等式约束的惩罚项,不包含界约束及不等式约束的惩罚项.原问题的解由求解一系列界约束极小化子问题而非无约束极小化子问题来获得.最后,用一类规模可变的非线性规划问题和一类最优控制问题对SBCMM进行了测试.数值结果表明,SBCMM可用于大规模过程系统优化求解,并且是稳定和有效的.

Based on sequential bound unconstrained minimization method of the nonlinear constraints,the sequential bound constrained minimization method（SBCMM） of steady-state optimization of large-scale process systems is studied.After applying relaxation variables to the engineering model,the penalty function of SBCMM only contains the penalty items about equality constraints but not the the ones about bound or inequality constraints.The solution of the original problem is obtained by solving a series of bound constrained minimization sub-problems but not by unconstrained minimization sub-problems.Finally,SBCMM is tested by a scale-variable nonlinear programming problem and an optimal control problem.The numerical results show that SBCMM is applicable to optimization solution of large-scale process systems and has the stability and effectiveness.