On the stochastic optimization problems of plastic metal-working processes

1997 ◽  
Vol 84 (3) ◽  
pp. 1109-1112 ◽  
Author(s):  
M. B. Gitman ◽  
P. V. Trusov ◽  
S. A. Fedoseev
Author(s):  
M. Hoffhues ◽  
W. Römisch ◽  
T. M. Surowiec

AbstractThe vast majority of stochastic optimization problems require the approximation of the underlying probability measure, e.g., by sampling or using observations. It is therefore crucial to understand the dependence of the optimal value and optimal solutions on these approximations as the sample size increases or more data becomes available. Due to the weak convergence properties of sequences of probability measures, there is no guarantee that these quantities will exhibit favorable asymptotic properties. We consider a class of infinite-dimensional stochastic optimization problems inspired by recent work on PDE-constrained optimization as well as functional data analysis. For this class of problems, we provide both qualitative and quantitative stability results on the optimal value and optimal solutions. In both cases, we make use of the method of probability metrics. The optimal values are shown to be Lipschitz continuous with respect to a minimal information metric and consequently, under further regularity assumptions, with respect to certain Fortet-Mourier and Wasserstein metrics. We prove that even in the most favorable setting, the solutions are at best Hölder continuous with respect to changes in the underlying measure. The theoretical results are tested in the context of Monte Carlo approximation for a numerical example involving PDE-constrained optimization under uncertainty.


2012 ◽  
Vol 215-216 ◽  
pp. 133-137
Author(s):  
Guo Shao Su ◽  
Yan Zhang ◽  
Zhen Xing Wu ◽  
Liu Bin Yan

Covariance matrix adaptation evolution strategy algorithm (CMA-ES) is a newly evolution algorithm. It has become a powerful tool for solving highly nonlinear multi-peak optimization problems. In many real-world optimization problems, the location of multiple optima is often required in a search space. In order to evaluate the solution, thousands of fitness function evaluations are involved that is a time consuming or expensive processes. Therefore, conventional stochastic optimization methods meet a special challenge for a very large number of problem function evaluations. Aiming to overcome the shortcoming of stochastic optimization methods in the high calculation cost, a truss optimal method based on CMA-ES algorithm is proposed and applied to solve the section and shape optimization problems of trusses. The study results show that the method is feasible and has the advantages of high accuracy, high efficiency and easy implementation.


Author(s):  
S.M. Vaytsekhovich ◽  
Yu.V. Vlasov ◽  
A.Yu. Zhuravlev

The production of semi-finished products made of refractory metals is considered. The advantage of parts production using combination of two types of straining with change in the straining direction: direct extrusion and equal-channel pressing is shown. The experimental investigation data of pure and simple shear for the semi-finished products processing made of tungsten and molybdenum are presented. Requirements for the tool providing diagonal flow and angular straining are formulated based on the analysis of the stress-strain state of the processes of axial symmetric extrusion and simple shear of plastically inhomogeneous body. Effectiveness evaluation of the combination of various types of fixtures and the rational sequence for using of diagonal flow and angular pressing is given. Experimental devices for practical application of the proposed technology are developed.


2021 ◽  
Author(s):  
Xiting Gong ◽  
Tong Wang

Preservation Results for Proving Additively Convex Value Functions for High-Dimensional Stochastic Optimization Problems


2018 ◽  
Vol 58 (11) ◽  
pp. 1728-1736 ◽  
Author(s):  
A. S. Bayandina ◽  
A. V. Gasnikov ◽  
E. V. Gasnikova ◽  
S. V. Matsievskii

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