Abstract
In this paper, by extending concept of the supermemory gradient method for unconstrained optimization problems, we present a supermemory gradient projection algorithm for nonlinear programming with nonlinear constraints. Under some suitable conditions we prove its global convergence.
Similar content being viewed by others
References
A. Miele, J.W. Cantrell, Study on a Memory Gradient Method for the Minimization of Functions,J.O.T.A.,3:6 (1969), 457–470.
E.E. Cragg, A.V. Levy, Study on a Supermemory Gradient Method for the Minimization of Functions,J.O.T.A.,4:3 (1969), 191–205.
Zhang Jincheng, A Memory Gradient Projection Method,Appl. Math. A Journal of Chinese Universities,3:2 (1988), 249–255 (in Chinese).
Du Dingzhu, A Gradient Projection Algorithm for Nonlinear Constraints,Acta Math. Appl. Sinica,8:1 (1985), 7–16 (in Chinese).
M.S. Bazaraa, C.M. Shetty, Nonlinear Programming, Theory and Algorithms, John Wiley and Sons, Inc. 1979.
Du Dingzhu, Sun Jie, A New Gradient Projection Method,Math. Numer. Sinica,6:4 (1984), 378–386 (in Chinese).
Gao Ziyou, The Feasible Direction Methods for Nonlinear Programming with Nonlinear Constraints, M.S. Thesis, Institute of Applied Mathematics, Academia Sinica, Beijing, 1988.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Gao, Z., He, G. A supermemory gradient projection algorithm for optimization problem with nonlinear constraints. Acta Mathematicae Applicatae Sinica 8, 323–332 (1992). https://doi.org/10.1007/BF02006741
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF02006741