scholarly journals Sample-Path Solutions for Simulation Optimization Problems and Stochastic Variational Inequalities

1998 ◽  
pp. 169-188 ◽  
Author(s):  
Gül Gürkan ◽  
A. Yonca Özge ◽  
Stephen M. Robinson
Keyword(s):  
Variational Inequalities ◽  
Optimization Problems ◽  
Simulation Optimization ◽  
Sample Path ◽  
Stochastic Variational Inequalities

scholarly journals Random variational inequalities in the absence of sample path continuity

1995 ◽  
Vol 8 (1) ◽  
pp. 91-97 ◽  
Author(s):  
S. A. Elsanousi
Keyword(s):  
Variational Inequalities ◽  
Existence Of Solutions ◽  
Sample Path ◽  
Stochastic Variational Inequalities ◽  
Random Variational Inequalities

In this paper we investigate the existence of solutions to stochastic variational inequalities under conditions that are not imposed sample-path-wise.

scholarly journals Sample-path solution of stochastic variational inequalities

1999 ◽  
Vol 84 (2) ◽  
pp. 313-333 ◽  
Author(s):  
Gül Gürkan ◽  
A. Yonca Özge ◽  
Stephen M. Robinson
Keyword(s):  
Variational Inequalities ◽  
Sample Path ◽  
Stochastic Variational Inequalities

Solving simulation optimization problems on grid computing systems

2006 ◽  
Vol 32 (9) ◽  
pp. 688-700 ◽  
Author(s):  
Demetrio Laganá ◽  
Pasquale Legato ◽  
Ornella Pisacane ◽  
Francesca Vocaturo
Keyword(s):  
Grid Computing ◽  
Optimization Problems ◽  
Simulation Optimization ◽  
Computing Systems

ADAPTIVE OPERATOR EXTRAPOLATION METHOD FOR VARIATIONAL INEQUALITIES IN BANACH SPACES

2021 ◽  
Vol 5 ◽  
pp. 82-92
Author(s):  
Sergei Denisov ◽  
◽  
Vladimir Semenov ◽  
Keyword(s):  
Banach Space ◽  
Variational Inequalities ◽  
Banach Spaces ◽  
Operations Research ◽  
Optimization Problems ◽  
Metric Projection ◽  
Feasible Set ◽  
Uniformly Smooth ◽  
Developing Area ◽  
Lipschitz Operators

Many problems of operations research and mathematical physics can be formulated in the form of variational inequalities. The development and research of algorithms for solving variational inequalities is an actively developing area of applied nonlinear analysis. Note that often nonsmooth optimization problems can be effectively solved if they are reformulated in the form of saddle point problems and algorithms for solving variational inequalities are applied. Recently, there has been progress in the study of algorithms for problems in Banach spaces. This is due to the wide involvement of the results and constructions of the geometry of Banach spaces. A new algorithm for solving variational inequalities in a Banach space is proposed and studied. In addition, the Alber generalized projection is used instead of the metric projection onto the feasible set. An attractive feature of the algorithm is only one computation at the iterative step of the projection onto the feasible set. For variational inequalities with monotone Lipschitz operators acting in a 2-uniformly convex and uniformly smooth Banach space, a theorem on the weak convergence of the method is proved.

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