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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS BLP 4223 OPTIMIZATION ELECTIVE 2 0 0 2

Offered By

Computer Programming

Level of Course Unit

Short Cycle Programmes (Associate's Degree)

Course Coordinator

DOCTOR ÖZER KESTANE

Offered to

Course Objective

With this course students; to establish models in linear nonlinear problems and to obtain optimum solutions.

Learning Outcomes of the Course Unit

1   Gain the ability to set up and solve mathematical models. 2   Use optimizing techniques efficiently

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Concepts of modeling and simulation 2 Linear programming 3 Graphical solution 4 Simplex method 5 Duality and sensitivity analysis 6 Transportation models 7 Midterm 8 Midterm 9 Distribution problems 10 Integer programming 11 Classical optimization theory 12 Newton-Raphson method 13 Non-restrictive algorithms 14 Restricted algorithms

Recomended or Required Reading

To be announced.

Planned Learning Activities and Teaching Methods

1. Lectures 2. Case Study

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 FN Final 3 FCG FINAL COURSE GRADE VZ*0.40 + FN* 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) VZ*0.40 + BUT* 0.60 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Mid-term exam and final exams are measuring 2 learning outcomes in-class applications and this is the stage of the student to achieve the learning outcomes will be monitored.

Language of Instruction

Turkish

Course Policies and Rules

70% of the classes is compulsory to attend. Disciplinary investigation will be concluded with the opening of any act of dishonesty.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

Will be announced by the instructor at the beginning of all semester.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 12 2 24 Preparation for midterm exam 1 8 8 Preparation for final exam 1 16 16 Midterm 1 1 1 Final 1 1 1 TOTAL WORKLOAD (hours) 50

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 PO.14 PO.15 LO.1 1 1 1 LO.2 1 1 1