
doi: 10.1007/bf01585112
In this paper, we study both the local and global convergence of various iterative methods for solving the variational inequality and the nonlinear complementarity problems. Included among such methods are the Newton and several successive overrelaxation algorithms. For the most part, the study is concerned with the family of linear approximation methods. These are iterative methods in which a sequence of vectors is generated by solving certain linearized subproblems. Convergence to a solution of the given variational or complementarity problem is established by using three different yet related approaches. The paper also studies a special class of variational inequality problems arising from such applications as computing traffic and economic spatial equilibria. Finally, several convergence results are obtained for some nonlinear approximation methods.
nonlinear approximation methods, linear approximation methods, Variational inequalities (global problems) in infinite-dimensional spaces, variational inequality problem, traffic equilibria, nonlinear complementarity problems, computation of equilibria, economic spatial equilibria, global convergence, Numerical mathematical programming methods, local convergence, General equilibrium theory, various iterative methods, Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming), successive overrelaxation algorithms
nonlinear approximation methods, linear approximation methods, Variational inequalities (global problems) in infinite-dimensional spaces, variational inequality problem, traffic equilibria, nonlinear complementarity problems, computation of equilibria, economic spatial equilibria, global convergence, Numerical mathematical programming methods, local convergence, General equilibrium theory, various iterative methods, Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming), successive overrelaxation algorithms
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