International audienceThe papers in this special issue seek to report cutting edge research on stochastic simulation and optimisation methodologies, and their application to challenging SP problems that are not well addressed by existing methodologies
The focus of the present volume is stochastic optimization of dynamical systems in discrete time whe...
The course covers a variety of topics in stochastic optimization. To begin with, some ap-proaches to...
• Stochastic optimization refers to the minimization (or maximization) of a function in the presence...
International audienceThe papers in this special issue seek to report cutting edge research on stoch...
International audienceModern signal processing (SP) methods rely very heavily on probability and sta...
The Handbook of Simulation Optimization presents an overview of the state of the art of simulation o...
Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult ...
We present a review of methods for optimizing stochastic systems using simulation. The focus is on g...
This book addresses stochastic optimization procedures in a broad manner. The first part offers an o...
The special issue of Mathematical Problems in Engineering deals with the issues of modeling, optimiz...
This discussion paper for the SGO 2001 Workshop considers the process of investigating stochastic gl...
Abstract Stochastic Programming (SP) was first introduced by George Dantzig in the 1950’s. Since tha...
Optimization problems arising in practice involve random model parameters. This book features many i...
In this chapter, we describe, the structure of the stochastic optimization solver SQG (Stochastic Qu...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
The focus of the present volume is stochastic optimization of dynamical systems in discrete time whe...
The course covers a variety of topics in stochastic optimization. To begin with, some ap-proaches to...
• Stochastic optimization refers to the minimization (or maximization) of a function in the presence...
International audienceThe papers in this special issue seek to report cutting edge research on stoch...
International audienceModern signal processing (SP) methods rely very heavily on probability and sta...
The Handbook of Simulation Optimization presents an overview of the state of the art of simulation o...
Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult ...
We present a review of methods for optimizing stochastic systems using simulation. The focus is on g...
This book addresses stochastic optimization procedures in a broad manner. The first part offers an o...
The special issue of Mathematical Problems in Engineering deals with the issues of modeling, optimiz...
This discussion paper for the SGO 2001 Workshop considers the process of investigating stochastic gl...
Abstract Stochastic Programming (SP) was first introduced by George Dantzig in the 1950’s. Since tha...
Optimization problems arising in practice involve random model parameters. This book features many i...
In this chapter, we describe, the structure of the stochastic optimization solver SQG (Stochastic Qu...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
The focus of the present volume is stochastic optimization of dynamical systems in discrete time whe...
The course covers a variety of topics in stochastic optimization. To begin with, some ap-proaches to...
• Stochastic optimization refers to the minimization (or maximization) of a function in the presence...