ECTS - Algorithms and Optimization Methods
Algorithms and Optimization Methods (SE328) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Algorithms and Optimization Methods | SE328 | 6. Semester | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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CMPE226 |
Course Language | English |
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Course Type | Compulsory Departmental Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture. |
Course Lecturer(s) |
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Course Objectives | 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. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | 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 |
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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. |
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Other Sources | 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
Requirements | Number | Percentage of Grade |
---|---|---|
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 |
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Percentage of Final Work | 35 |
Total | 100 |
Course Category
Core Courses | X |
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Major Area Courses | |
Supportive Courses | |
Media and Managment Skills Courses | |
Transferable Skill Courses |
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. |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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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 |
Total Workload | 59 |