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IE 538

Course ID:
Course Code & Number
IE 538
Course Title
Discrete Optimization
Level
MS
Credit Hours/ ECTS Credits
(3+0+0) 3 TEDU Credits, 7.5 ECTS Credits
Year of Study:
Master
Semester:
Type of Course:
Elective
Mode of Delivery:
Face-to-face
Language of Instruction:
English
Pre-requisite / Co-requisite::
Pre-requisites: NONE
Co-requisites: NONE
Catalog Description
Modeling, relaxing and bounding techniques. Fundamental easy-to-solve problems. Matching and assignment problems. Dynamic programming. Complexity theory. Branch-and-bound method. Meta-heuristics such as tabu search, genetic algorithms and variable neighborhood search. Application examples.
Course Objectives

The fundamental goal of this course is to provide a framework to solve optimization problems with discrete or integer variables. The course aims to teach the modeling, relaxing and bounding techniques. The topics will also include complexity theory, cutting plane algorithms, heuristics and approximation algorithms.

Software Usage
Course Learning Outcomes

Upon succesful completion of this course, a student will be able to
1. Model optimization problems with discrete or integer variables. (e)
2. Use relaxing and bounding techniques in discrete models (e)
3. Apply heuristic methods and approximation algorithms to find good solutions to integer programming models (a)
4. Use the branch and bound algorithm and the cutting plane algorithm for solving integer programming problems. (e)
5. Analyze the efficiency and complexity of algorithms (b)

Learning Activities and Teaching Methods:
Telling/Explaining Discussion/Debate Reading Problem Solving Collaborating Case Study/Scenarion Analysis
Assessment Methods and Criteria:
Test / Exam Quiz Case Studies / Homework
Assessment Methods and Criteria Others:
Design Content
Recommended Reading
1. Nemhauser, G. L., Wolsey, L. A. (1999), Integer and Combinatorial Optimization, Wiley-Interscience. 2. Korte, B., Vygen, J. (2012), Combinatorial Optimization: Theory and Algorithms (Algorithms and Combinatorics), Springer. 3. Papadimitriou, C. H., Steiglitz, K. (1998), Combinatorial Optimization: Algorithms and Complexity, Dover Publications.
Required Reading
1. Wolsey, L. (1998), Integer Programming, Wiley & Sons.
Grading
Learning Activities and Teaching Methods Others:
Course Coordinator:
Student Workload:
WorkloadHrs
Case Study Analysis28
Team Meetings14
Course & Program Learning Outcome Matching: