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 | Accumulated knowledge on mathematics, science and mechatronics engineering; ability to apply the theoretical and applied knowledge to model and analyze mechatronics engineering problems. | |||||
| 2 | Ability to identify, define and formulate problems related to the field and to select and apply appropriate analysis and modeling methods to solve these problems. | |||||
| 3 | Ability to design a complex system, product, component or process to meet the requirements under realistic constraints and conditions; ability to apply contemporary design methodologies; ability to implement effective engineering creativity techniques in mechatronics engineering. (Realistic constraints and conditions may include economics, environment, sustainability, producibility, ethics, human health, social and political problems.) | |||||
| 4 | Ability to develop, select and use modern techniques, skills and tools for application of mechatronics engineering and robot technologies; ability to use information and communications technologies effectively. | |||||
| 5 | Ability to design and perform experiments, collect and analyze data and assess the results for investigated problems on mechatronics engineering and robot technologies. | |||||
| 6 | Ability to work effectively on intra-disciplinary and multi-disciplinary teams; ability for individual work; ability to communicate and collaborate/cooperate effectively with other disciplines and scientific/engineering domains or working areas, ability to work with other disciplines including electrical & electronics and computer engineering. | |||||
| 7 | Ability to express creative and original concepts and ideas effectively in Turkish and English language, oral and written, and technical drawings. | |||||
| 8 | Ability to reach information on different subjects required by the wide spectrum of applications of mechatronics engineering, criticize, assess and improve the knowledge-base; consciousness on the necessity of improvement and sustainability as a result of life-long learning; monitoring the developments on science and technology; awareness on entrepreneurship, innovative and sustainable development and ability for continuous renovation. | |||||
| 9 | Consciousness on professional and ethical responsibility, competency on improving professional consciousness and contributing to the improvement of profession itself. | |||||
| 10 | Knowledge on the applications at business life such as project management, risk management and change management and competency on planning, managing and leadership activities on the development of capabilities of workers who are under his/her responsibility working around a project. | |||||
| 11 | Knowledge about the global, social and individual effects of mechatronics engineering applications on the human health, environment and security and cultural values and problems of the era; consciousness on these issues; awareness of legal results 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 | ||