| Improved Dual Algorithm for Constrained Optimization Problems |
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| 引用本文： | HAN Hua HE Suxiang ZHANG Zigang. Improved Dual Algorithm for Constrained Optimization Problems[J]. 武汉大学学报:自然科学英文版, 2007, 12(2): 230-234. DOI: 10.1007/s11859-006-0027-z |
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| 作者姓名： | HAN Hua HE Suxiang ZHANG Zigang |
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| 作者单位： | [1]School of Management, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China [2]School of Science, Wuhan University of Technology, Wuhan 430070, Hubei, China |
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| 基金项目： | Supported by the National 863 Project （2003AA002030） |
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| 摘 要： | One class of effective methods for the optimization problem with inequality constraints are to transform the problem to a unconstrained optimization problem by constructing a smooth potential function. In this paper, we modifies a dual algorithm for constrained optimization problems and establishes a corresponding improved dual algorithm; It is proved that the improved dual algorithm has the local Q-superlinear convergence; Finally, we performed numerical experimentation using the improved dual algorithm for many constrained optimization problems, the numerical results are reported to show that it is valid in practical computation.
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| 关 键 词： | 约束优化问题 改良 对偶算法 局部Q-超线性收敛 |
| 文章编号： | 1007-1202（2007）02-0230-05 |
| 收稿时间： | 2006-04-11 |
Improved dual algorithm for constrained optimization problems |
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| Han Hua,He Suxiang,Zhang Zigang. Improved dual algorithm for constrained optimization problems[J]. Wuhan University Journal of Natural Sciences, 2007, 12(2): 230-234. DOI: 10.1007/s11859-006-0027-z |
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| Authors: | Han Hua He Suxiang Zhang Zigang |
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| Affiliation: | (1) School of Management, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China;(2) School of Science, Wuhan University of Technology, Wuhan, 430070, Hubei, China |
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| Abstract: | One class of effective methods for the optimization problem with inequality constraints are to transform the problem to a unconstrained optimization problem by constructing a smooth potential function. In this paper, we modifies a dual algorithm for constrained optimization problems and establishes a corresponding improved dual algorithm; It is proved that the improved dual algorithm has the local Q-superlinear convergence; Finally, we performed numerical experimentation using the improved dual algorithm for many constrained optimization problems, the numerical results are reported to show that it is valid in practical computation. |
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| Keywords: | improved dual algorithm constrained optimizationproblems local Q-superlinear convergence numerical results |
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