# Algorithms and Optimization Methods (SE328) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Algorithms and Optimization Methods SE328 6. Semester 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English Compulsory Departmental Courses Bachelor’s Degree (First Cycle) Face To Face Lecture. This course is designed to teach students how to analyze and design algorithms and measure their complexities. In addition, students will be able to implement optimization methods for optimization problems. The students who succeeded in this course; Measure the complexity of algorithms Analyze and design algorithms Implement efficient algorithms for the solution of real life computational problems Analyze, design and implement optimization methods Design and analysis of algorithms; mathematical complexity of algorithms; master theorem; decrease-and-conquer; divide-and-conquer; transform-and-conquer; introduction to some optimization techniques; dynamic programming; greedy technique; iterative improvement; coping with limitations of algorithm power.

### Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 The role of algorithms and Getting Started CLRS Ch 1-2
2 Growth of Functions, Asymptotic Notation CLRS Ch. 3
3 Solving Recurrences: Substitution Method CLRS Ch. 4
4 Solving Recurrences: Recursion-Tree Method, Master's Method CLRS Ch. 4
5 Brute Force and Exhaustive Search LVTN Ch. 3 & CLRS Ch. 22
6 Decrease-and-Conquer LVTN Ch. 4 & CLRS Ch. 22
7 Divide-and-Conquer LVTN Ch. 5 & CLRS Ch. 7
8 Transform-and-Conquer LVTN Ch. 6 & CLRS Ch. 6
9 Dynamic Programming LVTN Ch. 8 & CLRS Ch. 15
10 Dynamic Programming LVTN Ch. 8 & CLRS Ch. 15
11 Greedy Algorithms LVTN Ch. 9 & CLRS Ch. 16
12 Greedy Algorithms LVTN Ch. 9 & CLRS Ch. 16
13 Iterative Improvement: The Simplex Method LVTN Ch. 10
14 Limitations of Algorithm Power, Coping with the Limitations of Algorithm Power, P, NP, NP-Complete Problems LVTN Ch. 11
15 Final Exam
16 Final Exam

### Sources

Course Book 1. Anany Levitin, Introduction to the Design & Analysis of Algorithms, 3rd edi-tion, Pearson, 2012. 2. T.H.Cormen, C.E.Leiserson, R.L.Rivest and C.Stein: Introduction to Algorithms, MIT Press 2001. 3. E.Horowitz, S.Sahni: Fundamentals of Computer Algorithms, Computer Sci-ence Press, 1989. 4. E.Horowitz, S.Sahni, S.Rajasekeran, Computer Algorithms, ISBN: 978-0-929306-41-4, Silicon Press, 2008. 5. J.Kleinberg, E.Tardos, Algorithm Design, Addison – Wesley, ISBN: 0-321-29535-8, 2006. 6. A.V.Aho, J.E.Hopcroft, J.D.Ullman, The Design and Analysis of Computer Algo-rithms, Addison-Wesley Series in Computer Science and Information Pro-cessing, 1979. 7. S.S. Skiena, The Algorithm Design Manual, Springer – Verlag, New York, 1998.

### Evaluation System

Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 3 15
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 50
Final Exam/Final Jury 1 35
Toplam 6 100
 Percentage of Semester Work 65 35 100

### Course Category

Core Courses X

### The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Adequate knowledge in mathematics, science and computing fields; ability to apply theoretical and practical knowledge of these fields in solving engineering problems related to information systems. X
2 Ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. X
3 Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose. X
4 Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in information systems engineering applications; ability to use information technologies effectively. X
5 Ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the information systems discipline. X
6 Ability to work effectively in inter/inner disciplinary teams; ability to work individually.
7 a. Effective oral and written communication skills in Turkish; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. b. Knowledge of at least one foreign language; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8 Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development.
9 a. Ability to behave according to ethical principles, awareness of professional and ethical responsibility. b. Knowledge of the standards utilized in information systems engineering applications.
10 a. Knowledge on business practices such as project management, risk management and change management. b. Awareness about entrepreneurship, and innovation. c. Knowledge on sustainable development.
11 a. Knowledge of the effects of information systems engineering applications on the universal and social dimensions of health, environment, and safety. b. Awareness of the legal consequences of engineering solutions.

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 2 32
Presentation/Seminar Prepration
Project
Report
Homework Assignments 3 4 12
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury
Prepration of Final Exams/Final Jury 1 15 15