COURSE INFORMATION PACKAGE · IND 501

Linear Optimization

ECTS
6
Local Credit
3
Theory + Practice + Lab
3 + 0 + 0
Course Level
Masters Degree
Prerequisites
-
Semester
1

Weekly Contents

Theory Topics
Week Weekly Contents
1 Modeling of optimization problems (Bazaraa, Jarvis & Sherali, Chapter 1, Bertsimas & Tsitsiklis, Chapter 1)
2 Modeling of optimization problems (Bazaraa & Sherali, Chapter 1, Wolsey, Chapter 1) and solution through GAMS and MATLAB+CPLEX
3 Basic concepts in linear algebra (Bazaraa, Jarvis & Sherali, Chapter 2)
4 Basic concepts in convex analysis (Bazaraa, Jarvis & Sherali, Chapter 2)
5 The simplex and big-M algorithms (Bazaraa, Jarvis & Sherali, Chapter 3)
6 The two-phase algorithm, degeneration, cycling, and cycling prevention rules (Bazaraa, Jarvis & Sherali, Chapter 4)
7 Farkas’ lemma, Karush-Kuhn-Tucker optimality conditions (Bazaraa, Jarvis & Sherali, Chapter 5)
8 Midterm I
9 Duality and sensitivity analysis (Bazaraa, Jarvis & Sherali, Chapter 6, Bertsimas & Tsitsiklis, Chapter 4)

Assessment System

Contribution to Overall Grade
Activities Number Contribution
Contribution of in-term studies to overall grade 0 0
Contribution of final exam to overall grade 0 0
Total 0 0
In-Term Studies
Activities Number Contribution
Assignments 0 0
Presentation 0 0
Midterm Examinations (including preparation) 0 0
Project 0 0
Laboratory 0 0
Other Applications 0 0
Quiz 0 0
Term Paper/ Project 0 0
Portfolio Study 0 0
Reports 0 0
Learning Diary 0 0
Thesis/ Project 0 0
Seminar 0 0
Other 0 0
Total 0 0

Relation of Proficiency

No Program Learning Outcomes Contribution
1 2 3 4 5
1
2
3
4 X
5 X
6 X
7 X
8
9 X
10 X
11 X
12

ECTS

Activities Number Period Total Workload
Class Hours 14 3 42
Working Hours out of Class 12 3 36
Assignments 5 10 50
Midterm Examinations (including preparation) 2 10 20
Other Applications 1 17 17
Total Workload 165
Total Workload / 25 6.60
Credits ECTS 7