| A CLASS OF TRUST REGION METHODS FOR LINEAR INEQUALITY CONSTRAINED OPTIMIZATION AND ITS THEORY ANALYSIS：Ⅰ. ALGORITHM AND GLOBAL CONVERGENCE |
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| 引用本文： | XIUNAIHUA. A CLASS OF TRUST REGION METHODS FOR LINEAR INEQUALITY CONSTRAINED OPTIMIZATION AND ITS THEORY ANALYSIS：Ⅰ. ALGORITHM AND GLOBAL CONVERGENCE[J]. 高校应用数学学报(英文版), 1995, 10(3): 287-296. DOI: 10.1007/BF02662871 |
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| 作者姓名： | XIUNAIHUA |
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| 作者单位： | InstituteofAppliedMathematics,AcademiaSinica,Beijing100080 |
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| 摘 要： | A class of trust region methods tor solving linear inequality constrained problems is propo6ed in this paper. It is shown that the algorithm is of global convergence. The algorithm uses a version of the two-slded projection and the strategy of the unconstrained trust region methods. It keeps the good convergence properties of the unconstrained case and has the merits of the projection method. In some sense, our algorithm can be regarded as an extension and improvement of the projected type algorithm.
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| 关 键 词： | 置信域法 线性不等式 约束最优化 全局收敛性 |
| 收稿时间： | 1993-10-11 |
A class of trust region methods for linear inequality constrained optimization and its theory analysis: I. Algorithm and global convergence |
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| Xiu Naihua. A class of trust region methods for linear inequality constrained optimization and its theory analysis: I. Algorithm and global convergence[J]. Applied Mathematics A Journal of Chinese Universities, 1995, 10(3): 287-296. DOI: 10.1007/BF02662871 |
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| Authors: | Xiu Naihua |
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| Affiliation: | (1) Institute of Applied Mathematics, Academia Sinica, 100080 Beijing;(2) Present address: Department of Mathematics, Hebei Teacher’s College, 050091 Shijiazhuang |
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| Abstract: | A class of trust region methods for solving linear inequality constrained problems is proposed in this paper. It is shown that the algorithm is of global convergence. The algorithm uses a version of the two-sided projection and the strategy of the unconstrained trust region methods. It keeps the good convergence properties of the unconstrained case and has the merits of the projection method. In some sense, our algorithm can be regarded as an extension and improvement of the projected type algorithm. |
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| Keywords: | 90C30 65D |
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