1	Course Title:	DESIGN AND ANALYSIS OF ALGORITHMS
2	Course Code:	END5121
3	Type of Course:	Optional
4	Level of Course:	Second Cycle
5	Year of Study:	1
6	Semester:	1
7	ECTS Credits Allocated:	7,5
8	Theoretical (hour/week):	3
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:	None
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Prof. Dr. ERDAL EMEL
16	Course Lecturers:
17	Contactinformation of the Course Coordinator:	erdal@uludag.edu.tr Tel: 0224 294 2080 Endüstri Mühendisliği Bölümü, Mühendislik Mimarlık Fakültesi Uludağ Üniversitesi, Görükle, Bursa
18	Website:
19	Objective of the Course:	Computer programs have an indisputable importance for almost all engineering applications. Programs have their basis from the algorithms. Regardless of the type of problems for different applications, there are always common things in algorithms. In this course, especially for optimization practices, it is aimed for Industrial Engineering students' to gain knowledge and skills on analytical thinking and practice for developing new algorithms.
20	Contribution of the Course to Professional Development

21

Learning Outcomes:

1 To gain necessary skills for algorithm design and coding through homework and projects on Visual Basic and Matlab;

22	Course Content:

Week	Theoretical	Practical
1	Algorithm definition, algorithmic problem solving, problem-types, data types.
2	The effectiveness of two algorithms: asymptotic representation, recursive and non-recursive Algorithms in mathematical analysis
3	Brute force, exhaustive research algorithms
4	Divide and Conquer algorithms: associative sort, quick sort, binary search
5	Decrease-and-conquer algorithms: insertion sort, Depth-First Search, Breadth-First search, topological sorting.
6	Simplify and conquer: pre-order, Gauss elimination, balanced search trees, vertical sorting.
7	Size and duration swaps: string matching, hashing, binary tree structures.
8	Dynamic programming algorithms: Floyd, back-pack
9	Greedy algoritms: Prim, Kruskal, Dikstra
10	Iterative improvement algorithms: Simplex, Maximum Flow Problem
11	Algorithm Limits: lower-limit, the decision trees, P, NP, and NP-complete problems.
12	Algorithmic constraints combat: backtracking
13	Branch and Bound
14	Approximation algorithms for NP-hard problems

23	Textbooks, References and/or Other Materials:	• Introduction to the Design and Analysis of Algorithms, Anany V. Levitin, Pearson Higher Education, 2007. • Introduction to Algorithms, T.H. Cormen, C.H. Leiserson, R.L. Rivest, C. Stein, McGrawHill, 2007.
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	1	30
Quiz	0	0
Homeworks, Performances	3	40
Final Exam	1	30
Total	5	100
Contribution of Term (Year) Learning Activities to Success Grade		70
Contribution of Final Exam to Success Grade		30
Total		100
Measurement and Evaluation Techniques Used in the Course
Information

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ECTS / WORK LOAD TABLE

Activites	NUMBER	TIME [Hour]	Total WorkLoad [Hour]
Theoretical	14	3	42
Practicals/Labs	0	0	0
Self Study and Preparation	14	5	70
Homeworks, Performances	3	20	40
Projects	1	30	30
Field Studies	0	0	0
Midtermexams	1	20	20
Others	0	0	0
Final Exams	1	20	20
Total WorkLoad			222
Total workload/ 30 hr			7,4
ECTS Credit of the Course			7,5

26	CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 PQ7 PQ8 PQ9 PQ10 PQ11 PQ12 PQ13 LO1 0 4 3 0 2 0 0 0 0 5 0 3 0

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High