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Improved Dual Algorithm for Constrained Optimization Problems
作者姓名:HAN  Hua  HE  Suxiang  ZHANG  Zigang
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
基金项目:Supported by the National 863 Project (2003AA002030)
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.

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
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.
Authors:Han Hua  He Suxiang  Zhang Zigang
Institution:(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
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.
Keywords:improved dual algorithm  constrained optimizationproblems  local Q-superlinear convergence  numerical results
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