Stochastic optimization methods are now being widely used in a multitude of applications. This dissertation includes three essays on applying stochastic optimization methods to solve problems in inventory management and financial engineering. Essay one addresses the problem of simultaneous price determination and inventory management. Demand depends explicitly on the product price p, and the inventory control system operates under a periodic review (s, S) ordering policy. To minimize the long-run average loss, we derive sample path derivatives that can be used in a gradient-based algorithm for determining the optimal values of the three parameters (s, S, p) in a simulation-based optimization procedure. Numerical results for several optimiza...
My PhD thesis concentrates on the field of stochastic analysis, with focus on stochastic optimizatio...
In initial work, we found a version of Retrospective Optimization, in which we optimize over a singl...
One of the significant challenges when solving optimization problems is ad-dressing possible inaccur...
Stochastic optimization methods are now being widely used in a multitude of applications. This disse...
Ideas of stochastic control have found applications in a variety of areas. A subclass of the problem...
Stochastic optimization is an effective tool for analyzing decision problems under uncertainty. In s...
This thesis is divided into three parts. The first part investigates the presence of long term depen...
Portfolio management problems can be broadly divided into two classes of differing investing styles:...
The scope of this volume is primarily to analyze from different methodological perspectives similar...
Research conducted in mathematical finance focuses on the quantitative modeling of financial markets...
This thesis addresses the topic of decision making under uncertainty, with particular focus on finan...
This project covers the basics of Financial Portfolio Management theory through different stochastic...
summary:The paper deals with a new stochastic optimization model, named OMoGaS–SV (Optimization Mode...
textStochastic control is a broad tool with applications in several areas of academic interest. The...
The Handbook of Simulation Optimization presents an overview of the state of the art of simulation o...
My PhD thesis concentrates on the field of stochastic analysis, with focus on stochastic optimizatio...
In initial work, we found a version of Retrospective Optimization, in which we optimize over a singl...
One of the significant challenges when solving optimization problems is ad-dressing possible inaccur...
Stochastic optimization methods are now being widely used in a multitude of applications. This disse...
Ideas of stochastic control have found applications in a variety of areas. A subclass of the problem...
Stochastic optimization is an effective tool for analyzing decision problems under uncertainty. In s...
This thesis is divided into three parts. The first part investigates the presence of long term depen...
Portfolio management problems can be broadly divided into two classes of differing investing styles:...
The scope of this volume is primarily to analyze from different methodological perspectives similar...
Research conducted in mathematical finance focuses on the quantitative modeling of financial markets...
This thesis addresses the topic of decision making under uncertainty, with particular focus on finan...
This project covers the basics of Financial Portfolio Management theory through different stochastic...
summary:The paper deals with a new stochastic optimization model, named OMoGaS–SV (Optimization Mode...
textStochastic control is a broad tool with applications in several areas of academic interest. The...
The Handbook of Simulation Optimization presents an overview of the state of the art of simulation o...
My PhD thesis concentrates on the field of stochastic analysis, with focus on stochastic optimizatio...
In initial work, we found a version of Retrospective Optimization, in which we optimize over a singl...
One of the significant challenges when solving optimization problems is ad-dressing possible inaccur...