| AN EFFECTIVE SEQUENTIAL QUADRATIC PROGRAMMING ALGORITHM FOR NONLINEAR OPTIMIZATION PROBLEMS |
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| 作者姓名： | 贺国平 高自友 郑永果 |
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| 作者单位： | 贺国平,郑永果(School of Information Science and Engineering, Shandong University of Science and Technology, Taian 271019);高自友(Northern Jiaotong University, Beijing 100044)
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| 基金项目： | This research was supported by the National Natural Science Foundation of China and the Natural Science Foundation of Shandong Province. |
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| 摘 要： | In this paper,a new globally convergent algorithm for nonlinear optimization prablems with equality and inequality constraints is presented. The new algorithm is of SQP type which determines a search direction by solving a quadratic programming subproblem per itera-tion. Some revisions on the quadratic programming subproblem have been made in such a way that the associated constraint region is nonempty for each point x generated by the algorithm, i. e. , the subproblems always have optimal solutions. The new algorithm has two important properties. The computation of revision parameter for guaranteeing the consistency of quadratic sub-problem and the computation of the second order correction step for superlinear convergence use the same inverse of a matrix per iteration, so the computation amount of the new algorithm will not be increased much more than other SQP type algorithms; Another is that the new algorithm can give automatically a feasible point as a starting point for the quadratic subproblems pe
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AN EFFECTIVE SEQUENTIAL QUADRATIC PROGRAMMING ALGORITHM FOR NONLINEAR OPTIMIZATION PROBLEMS |
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| He Guoping,Gao Ziyou,Zheng Yongguo.AN EFFECTIVE SEQUENTIAL QUADRATIC PROGRAMMING ALGORITHM FOR NONLINEAR OPTIMIZATION PROBLEMS[J].Numerical Mathematics A Journal of Chinese Universities English Series,2002,11(1):34-51. |
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| Authors: | He Guoping Gao Ziyou Zheng Yongguo |
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| Institution: | 1. School of Information Science and Engineering, Shandong University of Science and Technology, Taian 271019
2. Northern Jiaotong University, Beijing 100044 |
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| Abstract: | In this paper, a new globally convergent algorithm for nonlinear optimization problems with equality and inequality constraints is presented. The new algorithm is of SQP type which determines a search direction by solving a quadratic programming subproblem per itera-tion. Some revisions on the quadratic programming subproblem have been made in such a way that the associated constraint region is nonempty for each point x generated by the algorithm, i. e. , the subproblems always have optimal solutions. The new algorithm has two important properties. The computation of revision parameter for guaranteeing the consistency of quadratic sub-problem and the computation of the second order correction step for superlinear convergence use the same inverse of a matrix per iteration, so the computation amount of the new algorithm will not be increased much more than other SQP type algorithms ; Another is that the new algorithm can give automatically a feasible point as a starting point for the quadratic subproblems per iteration , this will obivously simplify the computation procedure of the subproblems. Some numerical results are reported. |
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| Keywords: | constrained optimization SQP method consistency feasible method one-step superlinear convergence |
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