ECTS - Heuristic Methods for Optimization
Heuristic Methods for Optimization (IE420) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Heuristic Methods for Optimization | IE420 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Discussion, Question and Answer, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | Upon successful completion of this course, students should gain knowledge of how and why heuristic techniques work, when they should be applied and their relative merits with respect to each other and with respect to more traditional approaches, such as mathematical programming. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Introduction of a variety of important, main-stream heuristic techniques, both traditional and modern, for solving combinatorial problems; reasons for the existence of heuristic techniques, their applicability and capabilities. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction: computational growth rate, algorithmic complexity and combinatorial problem | |
| 2 | Branch-and-Bound: branching, bounding, node development | |
| 3 | Dominance, relaxation to provide bounds and integer programming | |
| 4 | Lagrangian relaxation method | |
| 5 | Lagrangian relaxation method | |
| 6 | Local search: neighborhoods, local and global optimality, constructive and improvement heuristic techniques | |
| 7 | Local search: neighborhoods, local and global optimality, constructive and improvement heuristic techniques | |
| 8 | Simulated annealing: general approach, cooling schedules and variants | |
| 9 | Genetic algorithms: populations, reproduction, crossover | |
| 10 | Midterm | |
| 11 | Mutation, demes, competition and genetic programming | |
| 12 | TABU search: short term memory, TABU status, aspiration, intensification and diversification | |
| 13 | TABU search: short term memory, TABU status, aspiration, intensification and diversification | |
| 14 | Other methods and techniques: neural networks, random methods, hybrid methods | |
| 15 | Great Deluge algorithm, record-to-record transfer and parallel implementation | |
| 16 | Final Examination Period |
Sources
| Course Book | 1. Reeves, C. R., Modern Heuristic Techniques for Combinatorial Problems, John Wiley & Sons, 1993. |
|---|---|
| Other Sources | 2. Sait, S.M., and Youssef, H., Iterative Algorithms with Applications in Engineering, IEEE Press, 1999. |
| 3. Papadimitriou, C.H., and Steiglitz, K., Combinatorial Optimization: Algorithms and Complexity, Prentice-Hall, 1982. | |
| 4. Nemhauser, G.L., and Wolsey, L.A., Integer and Combinatorial Optimization, John Wiley & Sons, 1998. | |
| 5. Lawler, E.L., Lenstra, J.K., Rinnooy Kan, A.H.G., and Shmoys, D.B., The Traveling Salesman Problem, John Wiley & Sons, 1985. |
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 | 1 | 20 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 25 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 6 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| 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 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | |||||
| 2 | Ability to formulate, and solve complex mechatronics engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | |||||
| 3 | Ability to design a complex mechatronics engineering system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | |||||
| 4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in mechatronics engineering and robot technology practices; ability to employ information technologies effectively. | |||||
| 5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex mechatronics engineering and robot technology problems or research questions. | |||||
| 6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | |||||
| 7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | |||||
| 8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself | |||||
| 9 | a-) Knowledge on behavior according to ethical principles, professional and ethical responsibility b-) Knowledge on standards used in engineering practices. | |||||
| 10 | a-) Knowledge about business life practices such as project management, risk management, and change management b-) Awareness in entrepreneurship, innovation; knowledge about sustainable development. | |||||
| 11 | Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. | |||||
| 12 | Competency on defining, analyzing and surveying databases and other sources, proposing solutions based on research work and scientific results and communicate and publish numerical and conceptual solutions in the field of mechatronics engineering. | |||||
| 13 | Consciousness on the environment and social responsibility, competencies on observation, improvement and modify and implementation of projects for the society and social relations and be an individual within the society in such a way that planning, improving or changing the norms with a criticism. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 3 | 48 |
| Presentation/Seminar Prepration | |||
| Project | 1 | 5 | 5 |
| Report | |||
| Homework Assignments | 3 | 3 | 9 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 5 | 5 |
| Prepration of Final Exams/Final Jury | 1 | 10 | 10 |
| Total Workload | 125 | ||