A New Globally Convergent Algorithm for Nonlinear Constrainted Optimization Problems
Received:April 23, 1990  
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Author NameAffiliation
Wei Zhenxin Dept. of Math.
Guangxi University
Nanning
China 
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Abstract:
      In order to guarantee the globally convergence of the diffenence type SQP methods whose recently gave for the nonlinear constrainted optimization problems, they use the technique of penalty functions, so they must to correct the penalty parameter carefully. In this paper, we present a method which not only do not depend on the penalty parameter and the correct matrix can not are positive, and it possesses global convergence property but also, and the form penalty functions are simple and the rate of smooth of it equals to the rate of constrainted functions.
Citation:
DOI:10.3770/j.issn:1000-341X.1992.01.013
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