A Gradient Projection Algorithm Using the Fisher Function for Solving the Nonlinear Inequality Constrained Optimization Problem
Received:April 21, 2005  Revised:December 10, 2006
Key Words: nonlinear inequality constriants   gradient projection   the Fisher function   global convergence.  
Fund Project:Shanghai High Education Foundation for Development of Science and Technology (67ZZ83), the Natural Science Foundation of Guangxi Province (0542043) and the Youth Foundation of Guangxi Normal University.
Author NameAffiliation
ZHAO Yan College of Science, University of Shanghai for Science and Technology, Shanghai 200093, China
College of Mathematics and Information Science, Guangxi University, Guangxi 530004, China 
CHEN Cui-ling College of Mathematics Science, Guangxi Normal University, Guangxi 541004, China
College of Mathematics and Information Science, Guangxi University, Guangxi 530004, China 
WEI Zeng-xin College of Mathematics and Information Science, Guangxi University, Guangxi 530004, China 
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Abstract:
      A new two-stage search direction is proposed that combines the gradient projection and the Fisher function. Based on the new direction, this paper proposes a gradient projection algorithm for solving nonlinear inequality constrained optimization problem. The algorithm is shown to be globally convergent.
Citation:
DOI:10.3770/j.issn:1000-341X.2007.04.012
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