Course Name | Linear and Integer Programming |
Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
---|---|---|---|---|---|
CE 485 | Fall/Spring | 3 | 0 | 3 | 8 |
Prerequisites | None | |||||
Course Language | English | |||||
Course Type | Elective | |||||
Course Level | First Cycle | |||||
Mode of Delivery | - | |||||
Teaching Methods and Techniques of the Course | Problem SolvingLecture / Presentation | |||||
Course Coordinator | ||||||
Course Lecturer(s) | - | |||||
Assistant(s) | - |
Course Objectives | The primary objective is to develop both an understanding of the formulation techniques, and the algorithms used to solve the class of optimization problems that lend themselves to linear and integer linear programming. |
Learning Outcomes | The students who succeeded in this course;
|
Course Description | LP Standard Form, Extreme Points and Basic Solutions, Rudimentary Simplex Algorithm, Interior Point Strategies for LP, Formulating Duals, Primal-to-Dual Relationships, LP-Based Branch and Bound, and Rounding. |
Related Sustainable Development Goals | |
| Core Courses | |
Major Area Courses | X | |
Supportive Courses | ||
Media and Managment Skills Courses | ||
Transferable Skill Courses |
Week | Subjects | Required Materials |
1 | Nature of Linear Programs | Section 2.4 |
2 | Formulation of Classic LP Model Types | Chapter 4 |
3 | LP Standard Form, Extreme Points and Basic Solutions, Rudimentary Simplex Algorithm | Section 5.1, Section 5.2, Section 5.3 |
4 | Two Phase Simplex, Degeneracy, Cycling and Finiteness of Simplex | Section 5.5, Sections 5.6, Section 5.7 |
5 | Revised Simplex, Lower- and Upper-Bounded Simplex | Section 5.8, Section 5.9 |
6 | Interior Point Strategies for LP, Affine Scaling of Solutions, Affine Scaling Search | Section 6.1, Section 6.2, Section 6.3 |
7 | Log Barrier Methods for LP, Primal-Dual Search | Section 6.4, Section 6.5 |
8 | Midterm | |
9 | Activities vs. Resources, Qualititative Sensitivity | Sections 7.1-7.2 |
10 | Quantitative Sensitivity and Duality, Formulating Duals, Primal-to-Dual Relationships | Section 7.3, Section 7.4, Section 7.5 |
11 | Solving by Total Enumeration, Elementary Relaxations, Strengthening LP Relaxations | Section 12.1, Section 12.2, Section 12.3 |
12 | LP-Based Branch and Bound | Section 12.4 |
13 | Rounding, Parent Bounds, Enumeration Sequences and Stopping Early in Branch and Bound | Section 12.5 |
14 | Improving Heuristics for Discrete Optimization, Tabu, Simulated Annealing, Genetic Algorithms, Constructive Heuristics for Discrete Optimization | Section 12.6, Section 12.7, Section 12.8 |
15 | Review of semester | |
16 | Final Exam |
Course Notes/Textbooks | Optimization in Operations Research, Ronald L. Rardin, Prentice Hall, ISBN-10: 0023984155 • ISBN-13: 9780023984150, 1998. |
Suggested Readings/Materials |
Semester Activities | Number | Weigthing |
Participation | ||
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | ||
Portfolio | ||
Homework / Assignments | ||
Presentation / Jury | ||
Project | 1 | 30 |
Seminar / Workshop | ||
Oral Exam | ||
Midterm | 1 | 30 |
Final Exam | 1 | 40 |
Total |
Weighting of Semester Activities on the Final Grade | 2 | 60 |
Weighting of End-of-Semester Activities on the Final Grade | 1 | 40 |
Total |
Semester Activities | Number | Duration (Hours) | Workload |
---|---|---|---|
Course Hours (Including exam week: 16 x total hours) | 16 | 3 | 48 |
Laboratory / Application Hours (Including exam week: 16 x total hours) | 16 | ||
Study Hours Out of Class | 14 | 6 | 84 |
Field Work | |||
Quizzes / Studio Critiques | |||
Portfolio | |||
Homework / Assignments | |||
Presentation / Jury | |||
Project | 1 | 60 | |
Seminar / Workshop | |||
Oral Exam | |||
Midterms | 1 | 16 | |
Final Exams | 1 | 32 | |
Total | 240 |
# | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
1 | To have adequate knowledge in Mathematics, Science and Computer Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems. | X | ||||
2 | To be able to identify, define, formulate, and solve complex Computer Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose. | X | ||||
3 | To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose. | X | ||||
4 | To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Computer Engineering applications; to be able to use information technologies effectively. | X | ||||
5 | To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Computer Engineering research topics. | |||||
6 | To be able to work efficiently in Computer Engineering disciplinary and multi-disciplinary teams; to be able to work individually. | |||||
7 | To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions. | |||||
8 | To have knowledge about global and social impact of Computer Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Computer Engineering solutions. | |||||
9 | To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications. | |||||
10 | To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development. | |||||
11 | To be able to collect data in the area of Computer Engineering, and to be able to communicate with colleagues in a foreign language. ("European Language Portfolio Global Scale", Level B1) | |||||
12 | To be able to speak a second foreign language at a medium level of fluency efficiently. | |||||
13 | To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Computer Engineering. |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest