Operations Research Transactions ›› 2011, Vol. 15 ›› Issue (2): 28-44.
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JIAN Jin-Bao, WEI Xiao-Peng, ZENG Han-Jun, PAN Hua-Qin
Online:
Published:
Supported by:
Project (No.10771040) supported by NSFC, project (Nos.0832052) supported by Guangxi Science Foundation.
Abstract: In this paper, based on a semi-penalty function and an identification function used to yield a ``working set'', as well as the norm-relaxed SQP idea, a new algorithm for solving a kind of optimization problems with nonlinear equality and inequality constraints is proposed. At each iteration, to yield the search directions the algorithm solves only one reduced quadratic program (QP) subproblem and a reduced system of linear equations. The proposed algorithm possesses global convergence and superlinear convergence under some mild assumptions without the strictly complementarity. Finally, some elementary numerical experiments are reported.
Key words: integral tree, characteristic polynomial, diophantine equation, graph spectrum
JIAN Jin-Bao, WEI Xiao-Peng, ZENG Han-Jun, PAN Hua-Qin. A Norm-Relaxed Algorithm with Identification Function for General Constrained Optimization[J]. Operations Research Transactions, 2011, 15(2): 28-44.
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