This paper presents an augmented Lagrangian algorithm for nonlinear opti- mization of equality and bounded constraints. The method includes internal it- erations and outer iterations, which uses a trust region interio...This paper presents an augmented Lagrangian algorithm for nonlinear opti- mization of equality and bounded constraints. The method includes internal it- erations and outer iterations, which uses a trust region interior-point method in internal iteration. Under some conditions, the paper proves finite termination of internal iteration and analyses the local convergence of accelerating internal mini- mizer iterations. It also proves the global convergence of main algorithm when the approximate solution of internal minimizer is satisfied some conditions.展开更多
In this paper,the new SQP feasible descent algorithm for nonlinear constrained optimization problems presented,and under weaker conditions of relative,we proofed the new method still possesses global convergence and i...In this paper,the new SQP feasible descent algorithm for nonlinear constrained optimization problems presented,and under weaker conditions of relative,we proofed the new method still possesses global convergence and its strong convergence.The numerical results illustrate that the new methods are valid.展开更多
This paper considers dealing with path constraints in the framework of the improved control vector iteration （CVI） approach. Two available ways for enforcing equality path constraints are presented, which can be dir...This paper considers dealing with path constraints in the framework of the improved control vector iteration （CVI） approach. Two available ways for enforcing equality path constraints are presented, which can be directly incorporated into the improved CVI approach. Inequality path constraints are much more difficult to deal with, even for small scale problems, because the time intervals where the inequality path constraints are active are unknown in advance. To overcome the challenge, the ll penalty function and a novel smoothing technique are in-troduced, leading to a new effective approach. Moreover, on the basis of the relevant theorems, a numerical algo-rithm is proposed for nonlinear dynamic optimization problems with inequality path constraints. Results obtained from the classic batch reaCtor operation problem are in agreement with the literature reoorts, and the comoutational efficiency is also high.展开更多
文摘This paper presents an augmented Lagrangian algorithm for nonlinear opti- mization of equality and bounded constraints. The method includes internal it- erations and outer iterations, which uses a trust region interior-point method in internal iteration. Under some conditions, the paper proves finite termination of internal iteration and analyses the local convergence of accelerating internal mini- mizer iterations. It also proves the global convergence of main algorithm when the approximate solution of internal minimizer is satisfied some conditions.
基金Supported by the NNSF of China(10231060)Supported by the Soft Science Foundation of Henan Province(082400430820)
文摘In this paper,the new SQP feasible descent algorithm for nonlinear constrained optimization problems presented,and under weaker conditions of relative,we proofed the new method still possesses global convergence and its strong convergence.The numerical results illustrate that the new methods are valid.
基金Supported by the National Natural Science Foundation of China(U1162130)the National High Technology Research and Development Program of China(2006AA05Z226)Outstanding Youth Science Foundation of Zhejiang Province(R4100133)
文摘This paper considers dealing with path constraints in the framework of the improved control vector iteration （CVI） approach. Two available ways for enforcing equality path constraints are presented, which can be directly incorporated into the improved CVI approach. Inequality path constraints are much more difficult to deal with, even for small scale problems, because the time intervals where the inequality path constraints are active are unknown in advance. To overcome the challenge, the ll penalty function and a novel smoothing technique are in-troduced, leading to a new effective approach. Moreover, on the basis of the relevant theorems, a numerical algo-rithm is proposed for nonlinear dynamic optimization problems with inequality path constraints. Results obtained from the classic batch reaCtor operation problem are in agreement with the literature reoorts, and the comoutational efficiency is also high.
