Author： Gu Chao
Publisher： Taylor & Francis Ltd
ISSN： 0020-7160
Source： International Journal of Computer Mathematics, Vol.87, Iss.15, 2010-12, pp. : 3489-3506
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Abstract
In this paper, we propose a nonmonotone sequential quadratic programming-filter method for solving nonlinear equality constrained optimization. This new method has more flexibility for the acceptance of the trial step and requires less computational costs compared with the monotone methods. Under reasonable conditions, we give the global convergence properties. Further, the second-order correction step and nonmonotone reduction conditions are used to overcome Maratos effect so that quadratic local convergence is achieved. The numerical experiments are reported to show the effectiveness of the proposed algorithm.
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