| CODE | SOR5312 | ||||||||||||
| TITLE | Stochastic Programming 2 | ||||||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | ||||||||||||
| MQF LEVEL | 7 | ||||||||||||
| ECTS CREDITS | 10 | ||||||||||||
| DEPARTMENT | Statistics and Operations Research | ||||||||||||
| DESCRIPTION | Students taking this study-unit will be assigned a number of topics selected from the ones below which would cover topics of direct use to the particular student involved and which would make study-time demands commensurate with the number of credits being allotted: - Multistage stochastic programming 鈥� descriptive approach and underlying programs; - Selected stochastic programming models for finance, economics, and industry; - Principal deterministic reformulations applied to multistage stochastic programs; - Fundamental Theoretical Results (for example duality theory for multistage models); - Scenario-based programs and suitable solution techniques; - Robust Optimization approach to Stochastic Programming; - Advanced techniques: preprocessing and output analysis; - Advanced Stochastic Dynamic Programming methods. Study-Unit Aims: - Provide a sound background for those postgraduate students in probability, statistics and OR who would need knowledge of solving optimization problems involving random elements; - They would also be encouraged to gain practical expertise in using Stochastic Programming related algorithms in the course of computations related to research problems in the main areas of the department. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Comprehend the theoretical background and practical aspects of building Stochastic Programming models; - Get to grips with the results needed to know how the corresponding algorithm works and why and when it fails. 2. Skills: By the end of the study-unit the student will be able to: - Create and solve Stochastic Programming models related to the area the department specializes in; - Be able to use routines from standard software packages (MATLAB) and also specialized software to solve practical Stochastic Programming problems. Main Text/s and any supplementary readings: - Birge, J.R, Louveaux, F. (2000) Introduction to Stochastic Programming, Springer. - Kall, P, Wallace, S.W. (1995) Stochastic Programming, John Wiley & Sons. - Pr茅kopa, A. (1995) Stochastic Programming, Springer. - Kall, P., Mayer, J. (2005) Stochastic Linear Programming 鈥� Models, Theory and Computation, Springer. - Ermoliev, Y.M, Wets, R.J.B. (1989) Numerical Techniques for Stochastic Optimization Problems, Springer. - Bertsekas, D.P. (2005) Dynamic Programming and Optimal Control-Volume 1 and 2, Athena Scientific. - Wallace, S.W., Ziemba, W.T. (2005) Applications of Stochastic Programming, Society for Industrial and Applied Mathematic. Available at Department: - Dupacova, J., Hurt, J., Stepan, J. (2002) Stochastic Modeling in Economics and Finance, Springer. - Gosavi, A. (2003) Simulation-Based Optimization 鈥� Parametric Optimization and Reinforcement Learning, Kluwer Academic Publishers. - Bertsimas, D., Sim M. (2004) The Price of Robustness, Operations Research, Vol. 52, No. 1, pp. 35-53. - Ruszczynski, A., Shapiro, A. (2003) Handbooks in Operations Research and Management Science - Stochastic Programming, Elsevier. |
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| ADDITIONAL NOTES | Pre-requisite Study-unit: SOR2330, SOR3320 (SOR3350 from academic year 2022/2023 onwards) & SOR3311 | ||||||||||||
| STUDY-UNIT TYPE | Independent Study | ||||||||||||
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2025/6. It may be subject to change in subsequent years. |
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