Abstract. We describe algorithms for two-stage stochastic linear programming with recourse and their implementation on a grid computing platform. In particular, we examine serial and asynchronous versions of the L-shaped method and a trust-region method. The parallel platform of choice is the dynamic, heterogeneous, opportunistic platform provided by the Condor system. The algorithms are of master-worker type (with the workers being used to solve second-stage problems), and the MW runtime support library (which supports master-worker computations) is key to the implementation. Computational results are presented on large sample average approximations of problems from the literature. 1
Stochastic Programming (SP) has long been considered as a well-justified yet computationally challen...
Stochastic programming problems have very large dimension and characteristic structures which are tr...
Abstract: We present the mean value cross decomposition algorithm and its simple enhancement for the...
Abstract. We describe algorithms for two-stage stochastic linear programming with recourse and their...
We describe algorithms for two-stage stochastic linear programming with recourse and their implement...
In stochastic programming, the consideration of uncertainty might lead to large scale prob-lems. In ...
Stochastic linear programming problems are linear programming problems for which one or more data el...
Stochastic linear programs are linear programs in which some of the problem data are random variable...
2016-06-16Stochastic Programming (SP) has long been considered as a well-justified yet computational...
We develop scalable algorithms for two-stage stochastic program optimizations. We propose performanc...
This thesis presents a parallel algorithm for non-convex large-scale stochastic optimization problem...
Stochastic programming is a subfield of mathematical programming concerned with optimization problem...
We present a distributed asynchronous algorithm for solving two-stage stochastic mixed-integer progr...
Dynamic multistage stochastic linear programming has many practical applications for problems whose ...
The thesis deals with the algorithms for two-stage stochastic programs. The first chapter considers ...
Stochastic Programming (SP) has long been considered as a well-justified yet computationally challen...
Stochastic programming problems have very large dimension and characteristic structures which are tr...
Abstract: We present the mean value cross decomposition algorithm and its simple enhancement for the...
Abstract. We describe algorithms for two-stage stochastic linear programming with recourse and their...
We describe algorithms for two-stage stochastic linear programming with recourse and their implement...
In stochastic programming, the consideration of uncertainty might lead to large scale prob-lems. In ...
Stochastic linear programming problems are linear programming problems for which one or more data el...
Stochastic linear programs are linear programs in which some of the problem data are random variable...
2016-06-16Stochastic Programming (SP) has long been considered as a well-justified yet computational...
We develop scalable algorithms for two-stage stochastic program optimizations. We propose performanc...
This thesis presents a parallel algorithm for non-convex large-scale stochastic optimization problem...
Stochastic programming is a subfield of mathematical programming concerned with optimization problem...
We present a distributed asynchronous algorithm for solving two-stage stochastic mixed-integer progr...
Dynamic multistage stochastic linear programming has many practical applications for problems whose ...
The thesis deals with the algorithms for two-stage stochastic programs. The first chapter considers ...
Stochastic Programming (SP) has long been considered as a well-justified yet computationally challen...
Stochastic programming problems have very large dimension and characteristic structures which are tr...
Abstract: We present the mean value cross decomposition algorithm and its simple enhancement for the...