An improved sequential quadratic programming algorithm for solving general nonlinear programming problems

In this paper, a class of general nonlinear programming problems with inequality and equality constraints is discussed. Firstly, the original problem is transformed into an associated simpler equivalent problem with only inequality constraints. Then, inspired by the ideals of the sequential quadrati...

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Vydané v:Journal of mathematical analysis and applications Ročník 409; číslo 2; s. 777 - 789
Hlavní autori: Guo, Chuan-Hao, Bai, Yan-Qin, Jian, Jin-Bao
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Inc 15.01.2014
Predmet:
General nonlinear programming
Global convergence
Method of quasi-strongly sub-feasible directions
Sequential quadratic programming
Superlinear convergence
Superlinear convergence
Global convergence
General nonlinear programming
Sequential quadratic programming
Method of quasi-strongly sub-feasible directions
ISSN:0022-247X, 1096-0813
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Popis
Shrnutí:In this paper, a class of general nonlinear programming problems with inequality and equality constraints is discussed. Firstly, the original problem is transformed into an associated simpler equivalent problem with only inequality constraints. Then, inspired by the ideals of the sequential quadratic programming (SQP) method and the method of system of linear equations (SLE), a new type of SQP algorithm for solving the original problem is proposed. At each iteration, the search direction is generated by the combination of two directions, which are obtained by solving an always feasible quadratic programming (QP) subproblem and a SLE, respectively. Moreover, in order to overcome the Maratos effect, the higher-order correction direction is obtained by solving another SLE. The two SLEs have the same coefficient matrices, and we only need to solve the one of them after a finite number of iterations. By a new line search technique, the proposed algorithm possesses global and superlinear convergence under some suitable assumptions without the strict complementarity. Finally, some comparative numerical results are reported to show that the proposed algorithm is effective and promising.
ISSN:0022-247X
1096-0813
DOI:10.1016/j.jmaa.2013.06.052