COURSE UNIT TITLE

: MATHEMATICAL PROGRAMMING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BIL 2010 MATHEMATICAL PROGRAMMING COMPULSORY 4 0 0 7

Offered By

Computer Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASISTANT PROFESSOR AYŞE ÖVGÜ KINAY

Offered to

Computer Science

Course Objective

The objective of the course is to provide information about the establishment of linear and non-linear programming models, mathematical basis and solution algorithms of these models.

Learning Outcomes of the Course Unit

1   Be able to model various decision making problems.
2   Be able to solve the linear programming problem.
3   Be able to solve the nonlinear programming problem.
4   Be able to understand the importance of sensitivity analysis.
5   Be able to analyze and interpret the results.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Deterministic models
2 Linear decision models and examples
3 Fundamentals of linear programming and solution approaches
4 Simplex Algorithm
5 Big M Method and Two Phase Simplex Algorithm (Quiz-1)
6 Duality in Linear Programming
7 Sensitivity Analysis
8 Mid-term exam
9 Nonlinear Programming
10 Convex Sets Convex Functions
11 Fritz-John and Kuhn-Tucker Conditions
12 Problems with equality and inequality constraints (Quiz-2)
13 Lagrangian Duality Saddle Point
14 Optimality conditions Unconstrained optimization

Recomended or Required Reading

Textbook(s):
Taha, T.H., Yöneylem Araştırması; 6. Basımdan Çeviri, Literatür Yayıncılık, Istanbul, 2000.
Supplementary Book(s):
Kara, I., Doğrusal Programlama, Bilim Teknik Yayınevi, 2000.
Bazaraa, M.S., Shetty, C.M., Nonlinear Programming: Theory and Algorithms, John Wiley & Sons, 1979.

Planned Learning Activities and Teaching Methods

The course is taught in a lecture, class presentation and discussion format. Besides the taught lecture, group presentations are to be prepared by the groups assigned and presented in a discussion session. In some weeks of the course, results of the homework given previously are discussed.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + ASG * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.30 + RST * 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

ovgu.tekin@deu.edu.tr
cagin.kandemir@deu.edu.tr

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 4 52
Preparations before/after weekly lectures 12 4 48
Preparation for midterm exam 1 20 20
Preparation for final exam 1 30 30
Preparation for quiz etc. 2 4 8
Final 1 2 2
Midterm 1 2 2
Quiz etc. 2 1 2
TOTAL WORKLOAD (hours) 164

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13
LO.15554334
LO.2534
LO.3534
LO.44454334
LO.534455443