Stochastic Ellipsoid Methods with Multiple Cuts
نویسندگان
چکیده
منابع مشابه
Stochastic Ellipsoid Methods with Multiple Cuts
Robust control systems synthesis is generally recast as a class of robust feasibility problems which is to find a solution satisfying a set of parameter-dependent convex constraints for all possible parameter values. For this class of the problems, a stochastic ellipsoid method with multiple cuts each of which corresponds to each of the constraint is proposed, where a new update rule is present...
متن کاملNumerical methods for stochastic partial differential equations with multiple scales
A new method for solving numerically stochastic partial differential equations (SPDEs) with multiple scales is presented. The method combines a spectral method with the heterogeneous multiscale method (HMM) presented in [W. E, D. Liu, and E. Vanden-Eijnden, Comm. Pure Appl. Math., 58(11):1544–1585, 2005]. The class of problems that we consider are SPDEs with quadratic nonlinearities that were s...
متن کاملA new approach based on alpha cuts for solving data envelopment analysis model with fuzzy stochastic inputs and outputs
Data Envelopment Analysis (DEA) is a widely used technique for measuring the relative efficiencies of homogenous Decision Making Units (DMUs) with multiple inputs and multiple outputs. These factors may be evaluated in fuzzy or stochastic environment. Hence, the classic structures of DEA model may be changed where in two fold fuzzy stochastic environment. For instances, linearity, feasibility a...
متن کاملIIS Cuts for Stochastic Programs with Joint Chance-Constraints
We present a new method for solving stochastic programs with joint chance constraints with discretely distributed random data. The problem can be reformulated as a large-scale mixed 0-1 integer program. We derive a new class of optimality cuts based on irreducibly infeasible subsets (IIS) of an LP defined by requiring that all scenarios be satisfied and propose a method for improving the upper ...
متن کاملStrengthened Benders Cuts for Stochastic Integer Programs with Continuous Recourse
With stochastic integer programming as the motivating application, we investigate techniques to use integrality constraints to obtain improved cuts within a Benders decomposition algorithm. We compare the effect of using cuts in two ways: (i) cut-and-project, where integrality constraints are used to derive cuts in the extended variable space, and Benders cuts are then used to project the resul...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Transactions of the Institute of Systems, Control and Information Engineers
سال: 2008
ISSN: 1342-5668,2185-811X
DOI: 10.5687/iscie.21.145