sap course 1500382098

Course Code & Number:

IE 438

Course Title:

Discrete Optimization

Level of Course:

BS

Credits:

(3+0+0) 3 TEDU Credits, 5 ECTS Credits

Catalog Description:

Modeling, relaxing and bounding techniques. Fundamental easy-to-solve problems. Branch-and-bound, cutting planes method, branch and price and column generation methods. Dynamic programming. Meta-heuristics such as tabu search, genetic algorithms and variable neighborhood search. Application examples.

Pre-requisites & Co-requisites:

Pre-requisites: NONE
Co-requisites: NONE
Semester: 
Spring
Mode of Delivery: 
Face-to-face
Language of Instruction: 
English
Course Type: 
Elective
Required Reading: 
Course materials, lecture notes
Course Objective: 

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 cutting plane algorithms, heuristics and approximation.

Extended Description: 

Modeling, relaxing and bounding techniques. Fundamental easy-to-solve problems. Branch-and-bound, cutting planes method, branch and price and column generation methods. Dynamic programming. Meta-heuristics such as tabu search, genetic algorithms and variable neighborhood search. Application examples.

Computer Usage: 
PC, Laptop, Java ILOG Cplex, Gams
Learning Outcomes: 

Upon succesful completion of this course, a student will be able to

1. Model optimization problems with discrete or integer variables (c),

2. Use relaxing and bounding techniques in discrete models (c),

3. Apply heuristic methods and approximation algorithms to find good solutions to integer programming models (h),

4. Use the branch and bound algorithm and the cutting plane algorithm for solving integer programming problems (i).

Planned Learning Activities and Teaching Methods: 
Telling/Explaining
Discussion/Debate
Questioning
Reading
Problem Solving
Inquiry
Collaborating
Case Study/Scenarion Analysis
Hands-on Activities
Assessment Methods and Criteria: 
Test / Exam
Quiz/Homework
Labrotary Work
Written Project
Presentation (Oral/Poster)

Student Workload:

Quizzes /Homeworks
40
hrs
Midterm Exam 1
12
hrs
Final Exam
18
hrs
Research Review
5
hrs
Oral Presentation
5
hrs
Team Meetings
15
hrs
Others
50
hrs

Prepared By:

Vedat Bayram

Revised By:

Vedat Bayram