A new non-monotone filter trust region algorithm for solving nonlinear systems of equalities and inequalities
Abstract
In this paper, we combine filter and non-monotone trust region algorithm for nonlinear systems of equalities and inequalities. The systems of equalities and inequalities are transformed into a continuous equality constrained optimization solved by the new algorithm. Filter method guarantees global convergence of the algorithm under appropriate assumptions. The second order correction step is used to overcome Maratos effect so that superlinearly local convergence is achieved. Preliminary numerical results are reported.References
R.H.Byrd, Robust trust region methods for constrained optimization, in: Third SIAM Conference on Optimization, Houston, Texas, May, 1987.
C.M.Chin, A.H.A.Rashid, K.M.Nor, Global and local convergence of a filter line search method for nonlinear programming, Optimization Methods and Software. 22 (2006) 365-390.
A.R.Conn, N.I.M.Gould, Ph.L.Toint, Trust Region Methods, MPS/SIAM Ser. Optim. 1, SIAM, Philadelphia, 2000.
J.E.Dennis, M.El-Alem, K.Williamson, A trust-region approach to nonlinear systems of equalities and inequalities, SIAM J. Optim. 9 (1999) 291-315.
J.E.Dennis, M.EI-Alem, M.C.Maciel, A global convergence theory for general trust region based algorithms for equality constrained optimization, SIAM J. Optim. 7 (1997) 177-207.
R.Fletcher, S.Leyffer, Nonlinear programming without a penalty function. Math. Program. 91 (2002) 239-269.
R.Fletcher, S.Leyffer, P.L.Toint, On the global convergence of a filter-SQP algorithm. SIAM J. Optim. 13 (2002) 44-59 .
R.Fletcher, N.I.M.Gould, S.Leyffer, P.L.Toint, A.Wachter, Global convergence of a trust-region SQP-filter algorithm for general nonlinear programming. SIAM J. Optim. 13 (2002) 635-659.
C.Gu, D.Zhu, A filter interior-point algorithm with projected Hessian updating for nonlinear optimization, J. Appl. Math. Comput. 29 (2009) 67-80.
C.Gu, D.Zhu, A filter secant method with nonmonotone line search for equality constrained optimization, J. Syst. Sci. Complex 23 (2010) 846-860.
C.Gu, D.Zhu, A non-monotone line search multidimensional filter-SQP method for general nonlinear programming, Numer. Algor. 56 (2011) 537-559.
B.He, H.Yang, C.Zhang, A modified augmented Lagrangian method for a class of monotone variational inequalities, European J. Oper. Res. 159 (2004) 35-51.
C.J.Li, W.Y.Sun, On filter-successive linearization methods for nonlinear semidefinite programming, Sci China Ser A 52 (2009) 2341-2361.
M.Macconi, B.Morini, M.Porcelli, Trust-region quadratic methods for nonlinear systems of mixed equalities and inequalities, Appl. Numer. Math. 59 (2009) 859-876.
A.Mohamed, A weighted full-Newton step primal-dual interior point algorithm for convex quadratic optimization, Statistics, Optimization and Information Computing 2 (2014) 21-32.
P.Y.Nie, C.F.Ma, A trust region filter mehtod for general nonlinear programming, Appl. Math. Comput. 172 (2006) 1000-1017.
E.O.Omojokun, Trust region algorithms for optimization with nonlinear equality and inequality constraints, Ph.D. Thesis, University of Colorado, Boulder Colorado, USA, 1989.
L.Qi, D.Sun, G.Zhou, A new look at smoothing newton methods for nonlinear complementarity problems and box constrained variational inequality problems, Math. Program. 87 (2000) 1-35.
L.Qi, Y.Yang, NCP functions applied to Lagrangian globalization for the nonlinear complementarity problem, Journal of Global Optimization 24 (2) (2002) 261-283.
S.P.Rui, C.X.Xu, A smoothing inexact Newton method for nonlinear complementarity problems, J. Comput. Appl. Math. 233 (2010) 2332-2338.
W.Sun, Y.Yuan, Optimization Theory and Methods: Nonlinear Programming, Springer, New York, 2006.
W.Sun, Non-monotone trust region method for optimization, Appl. Math. Comput. 156 (2004) 159-174.
W.Sun, D.Xu, A filter trust-region method based on conic model for unconstrained optimization, Science China Mathematics, 55 (2012) 527-543.
Y,Chen, W.Sun, A dwindling filter line search method for unconstrained optimization, Mathematics of Compuation, 84 (2015) 187-208.
K.Su, Z.Yu, A modified SQP method with nonmonotone technique and its global convergence, Comput. Math. Appl. 57 (2009) 240-247.
K.Su, D.G.Pu, A nonmonotone filter trust region method for nonlinear constrained optimization, J. Comput. Appl. Math. 223 (2009) 230-239.
H.Wang, D.G.Pu, A nonmonotone filter trust region method for the system of nonlinear equations, Appl. Math. Model. 37 (2013) 498-506.
Y.J.Wang, D.Zhu, An affine scaling interior trust region method via optimal path for solving monotone variational inequality problem with linear constraints, Chin. Ann. Math. 29B (2008) 273-290.
A.Wachter, L.T.Biegler, Line search filter methods for nonlinear programming: Local convergence. SIAM J. Optim. 6: 32-48 (2005).
J.Wu, G.Yu, On the Convergence and O (1/N) Complexity of a Class of Nonlinear Proximal Point Algorithms for Monotonic Variational Inequalities, Statistics, Optimization and Information Computing, 2 (2014) 105-113.
L.Yang, Y.Chen, X.Tong, Smoothing newton-like method for the solution of nonlinear systems of equalities and inequalities, Numer. Math. Theor. Meth. Appl. 2 (2009) 224-236.
Y.Yuan, Trust region algorithms for nonlinear programming, in Computational Mathematics in China, Contemp. Math. 163, Z. C. Shi, ed., AMS, Providence, RI, 1994, 205-225.
H.Zhang, W.W.Hager, A nonmonotone line search technique and its application to unconstrained optimization, SIAM J. Optim. 14 (2004) 1043-1056.
Y.Zhang, Z.Huang, A nonmonotone smoothing-type algorithm for solving a system of equalities and inequalities, J. Comput. Appl. Math. 233 (2010) 2312-2321.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).