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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| INDUSTRIAL ENGINEERING (MASTER) (WITH THESIS) | |
| Code | EM014 |
| Name | Modern Heuristics |
| Term | 2018-2019 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Belirsiz |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. CENK ŞAHİN |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The aim of the course is to provide the students with the basic knowledge about heuristic algorithms, to follow the new developments in this field and to develop their ability to use heuristic algorithms for solving engineering problems. Thus, it is aimed that the students learn important topics about heuristic algorithms and use them in various economic areas.
Course Content
This course includes modern heuristics used for optimization purposes.
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Understanding the basic principles of heuristic techniques |
| LO02 | Ability to adapt heuristic methods to problems |
| LO03 | To understand the differences between heuristics techniques |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Understands, interprets and applies knowledge in his/her field domain both in-depth and in-breadth by doing scientific research in industrial engineering. | |
| PLO02 | - | Acquires comprehensive knowledge about methods and tools of industrial engineering and their limitations. | |
| PLO03 | - | Designs and performs analytical modeling and experimental research and analyze/solves complex matters emerged in this process. | |
| PLO04 | - | Completes and applies the knowledge by using scarce and limited resources in a scientific way and integrates the knowledge into various disciplines. | |
| PLO05 | - | Keeps up with the recent changes and applications in the field of Industrial Engineering and examines and learns these innovations when necessary. | |
| PLO06 | - | Has the ability to propose new and/or original ideas and methods, develops innovative solutions for designing systems, components or processes. | |
| PLO07 | - | Designs Industrial Engineering problems, develops innovative methods to solve the problems and applies them. | |
| PLO08 | - | Works in multi-disciplinary teams and takes a leading role and responsibility. | |
| PLO09 | - | Identifies, gathers and uses necessary information and data. | |
| PLO10 | - | Follows, studies and learns new and developing applications of industrial engineering. | |
| PLO11 | - | Uses a foreign language in verbal and written communication at least B2 level of European Language Portfolio. | |
| PLO12 | - | Presents his/her research findings systematically and clearly in oral and written forms in national and international platforms. | |
| PLO13 | - | Understands social and environmental implications of engineering practice. | |
| PLO14 | - | Considers social, scientific and ethical values in the process of data collection, interpretation and announcement of the findings. | |
| PLO15 | - | Works in multi-disciplinary teams, take a leading role and responsibility and develop solutions for complex problems. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to Heuristic Algorithms | Reading lecture resources and study notes | |
| 2 | modern search techniques | Reading lecture resources and study notes | |
| 3 | Tabu search | Reading lecture resources and study notes | |
| 4 | Simulated annealing | Reading lecture resources and study notes | |
| 5 | Genetic algorithm | Reading lecture resources and study notes | |
| 6 | Differential evolution algorithm | Reading lecture resources and study notes | |
| 7 | Ant colony | Reading lecture resources and study notes | |
| 8 | Mid-Term Exam | Reading lecture resources and study notes | |
| 9 | Particle swarm | Reading lecture resources and study notes | |
| 10 | Fuzzy logic | Reading lecture resources and study notes | |
| 11 | Artificial neural networks | Reading lecture resources and study notes | |
| 12 | Heuristic algorithm applications-1 | Reading lecture resources and study notes | |
| 13 | Heuristic algorithm applications-2 | Reading lecture resources and study notes | |
| 14 | Heuristic algorithm applications-3 | Reading lecture resources and study notes | |
| 15 | Heuristic algorithm applications-4 | Reading lecture resources and study notes | |
| 16 | Term Exams | Reading lecture resources and study notes | |
| 17 | Term Exams | Reading lecture resources and study notes |