Stochastic Optimization with Partial Information


This research has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARISTEIA II. Investing in knowledge society through the European Social Fund.



Project Title

Optimization of stochastic systems under partial information and applications.

Project Duration

1 year (November 2014-October 2015)

Keywords

Stochastic Optimization, Partial Information, Queueing Theory, Game Theory, Markov Decision Processes.

Summary

The goal of this research project is to develop innovative mathematical models for control of stochastic systems under partial information. Under this general framework, the research focuses on the following specific objectives, in which the common thread is the notion of incomplete information and adaptive optimization: The problems that are studied have wide applicability, ranging from production and supply chain management, design and control of service systems, resource allocation under incomplete information, etc. The methodologies that are used come from a variety of areas, namely Stochastic Operations Research and in particular Markov Decision Processes, Inventory Theory and Queueing Theory, Game Theory, and Probability and Statistics. The research project aspires to promote interdisciplinary collaboration in the area of Stochastic Optimization, by forming a research group whose members are faculty in Mathematics and Engineering in two universities.

Research Group



Publications (Papers)



Conference presentations (Slides)



Bibliography (References)


Last revision: September 10, 2015