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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS BIL 3006 COMBINATORIAL OPTIMIZATION COMPULSORY 4 0 0 7

Offered By

Computer Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ZEYNEP NIHAN BERBERLER

Offered to

Computer Science

Course Objective

To teach combinatorial optimization concepts to solve computer science problems.

Learning Outcomes of the Course Unit

1   Have a knowledge of basic concepts of combinatorial optimization. 2   Be able to solve problems of combinatorial optimization. 3   Be able to solve computer science problems by using combinatorial optimization concepts. 4   Be able to design efficient algorithms by using combinatorial optimization concepts. 5   Be able to solve problems of different type of disciplines by using concepts of combinatorial optimization.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Classifying Optimization Problems 2 Combinatorial Optimization Problems (Examples, Models) 3 Knapsack Problems 4 Travelling Salesman Problems, Quiz 1 5 Combinatorial Optimization Methods 6 Branch and Bound Method, 7 Solving Knapsack and Travelling Salesman Problems with Branch and Bound Method 8 Mid-term exam 9 Set Covering Problems 10 Machine Scheduling Problems 11 Dynamic Programming 12 Approximate Methods for Combinatorial Optimization Problems, Quiz 2 13 Greedy Algorithms 14 Greedy Algorithms for Knapsack Problems, Greedy Algorithms for Travelling Salesman Problems

Recomended or Required Reading

Textbook(s): Combinatorial Optimizaiton, William J. Cook, W.H.C., W.R.P., A.S., ISBN 047155894.

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 FIN FINAL EXAM 3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + FIN * 0.60 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

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)

zeynep.berberler@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 7 84 Preparation for midterm exam 1 12 12 Preparation for final exam 1 24 24 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 176

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 LO.1 4 LO.2 5 5 LO.3 4 5 5 LO.4 5 5 LO.5 5 5