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 |
|---|---|---|---|---|---|---|---|
| Algorithms and Optimization Methods | SE328 | 6. Semester | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| CMPE226 |
| Course Language | English |
|---|---|
| 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) |
|
| 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;
|
| 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 |
|---|---|---|
| 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. |
|---|---|
| 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 |
|---|---|
| Percentage of Final Work | 35 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| 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 | Gain sufficient knowledge in mathematics, science and computing; be able to use theoretical and applied knowledge in these areas to solve engineering problems related to information systems. | X | ||||
| 2 | To be able to identify, define, formulate and solve complex engineering problems; to be able to select and apply appropriate analysis and modeling methods for this purpose. | X | ||||
| 3 | Designs a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; applies modern design methods for this purpose. | X | ||||
| 4 | To be able to develop, select and use modern techniques and tools required for the analysis and solution of complex problems encountered in information systems engineering applications; to be able to use information technologies effectively. | X | ||||
| 5 | Designs and conducts experiments, collects data, analyzes and interprets results to investigate complex engineering problems or research topics specific to the discipline of information systems engineering. | X | ||||
| 6 | Can work effectively in disciplinary and multidisciplinary teams; can work individually. | |||||
| 7 | a. Communicates effectively both orally and in writing; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions. b. Knows at least one foreign language. | |||||
| 8 | To be aware of the necessity of lifelong learning; to be able to access information, to be able to follow developments in science and technology and to be able to renew himself/herself continuously. | |||||
| 9 | a. Acts in accordance with the principles of ethics, gains awareness of professional and ethical responsibility. b. Gains knowledge about the standards used in information systems engineering applications. | |||||
| 10 | a. Gains knowledge about business life practices such as project management, risk management and change management. b. Gains awareness about entrepreneurship and innovation. c. Gains knowledge about sustainable development. | |||||
| 11 | a. To be able to acquire knowledge about the universal and social effects of information systems engineering applications on health, environment and safety and the problems of the era reflected in the field of engineering. b. Gains awareness of the legal consequences of engineering solutions. | |||||
ECTS/Workload Table
| 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 |
| Total Workload | 59 | ||