IE560 STOCHASTIC PROGRAMMING
| Course Code: | 5680560 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Industrial Engineering |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Assist.Prof.Dr SAKİNE BATUN |
| Offered Semester: | Spring Semesters. |
Course Objectives
Upon successful completion of this course, the students are expected to:
- Learn to formulate problems with quantified uncertainty as stochastic programs.
- Learn the structural properties of two-stage stochastic linear programs and its extensions.
- Learn and gain experience in implementing various solution methods for stochastic programs.
- Set a foundation for future research in stochastic programming.
Course Content
Introduction to modeling under uncertainty. Basic properties of two-stage stochastic linear programs. Stage-wise and scenario-wise decomposition methods for solving two-stage stochastic linear programs. Value of capturing uncertainty. Chance-constrained stochastic programs. Multi-stage stochastic linear programs. Stochastic integer programs. Bounding and sampling methods.
Course Learning Outcomes
Upon successful completion of this course, students will be able to:
- Formulate real-world decision-making problems involving uncertainty as stochastic programming models.
- Analyze the structural properties of two-stage stochastic linear programs and their extensions.
- Implement and compare various solution methods for stochastic programs using appropriate computational tools.
- Demonstrate foundational knowledge necessary to pursue advanced study or research in stochastic programming.
Program Outcomes Matrix
| Contribution | |||||
| # | Program Outcomes | No | Yes | ||
| 1 | Specialize with advanced knowledge in selected areas of Industrial Engineering; such as Production and Operations Management, Supply Chain Management, Business Analytics and Information Systems, Decision Sciences and Operational Research, Quality Management, Human Factors and Ergonomics, and Strategy and Industrial Economics. | ✔ | |||
| 2 | Have advanced ability to formulate and solve industrial engineering problems. | ✔ | |||
| 3 | Be able to systematically acquire new scientific knowledge to design and improve socio-technical systems. | ✔ | |||
| 4 | Be able to conduct scientific research in industrial engineering. | ✔ | |||
| 5 | Be able to apply critical reasoning in their professional careers. | ✔ | |||
| 6 | Appreciate the academics ethics. | ✔ | |||