| Ders Adı | Kodu | Yarıyıl | T+U Saat | Kredi | AKTS |
|---|---|---|---|---|---|
| Sector Orıented Erp Applıcatıons | ENM 453 | 7 | 3 + 0 | 3 | 5 |
| Ön Koşul Dersleri | |
| Önerilen Seçmeli Dersler | |
| Dersin Dili | Türkçe |
| Dersin Seviyesi | Lisans |
| Dersin Türü | Seçmeli |
| Dersin Koordinatörü | Dr.Öğr.Üyesi NEVRA AKBİLEK |
| Dersi Verenler | Dr.Öğr.Üyesi NEVRA AKBİLEK, |
| Dersin Yardımcıları | |
| Dersin Kategorisi | Diğer |
| Dersin Amacı | |
| Dersin İçeriği |
| # | Ders Öğrenme Çıktıları | Öğretim Yöntemleri | Ölçme Yöntemleri |
|---|---|---|---|
| 1 | Be informed about introduction to optimization | Lecture, Question-Answer, Discussion, | Oral Exam, Homework, |
| 2 | Be informed about simulated annealing | Lecture, Question-Answer, Discussion, Problem Solving, | Homework, |
| 3 | Be informed about genetic algorithm | Lecture, Question-Answer, Problem Solving, Project Based Learning, | Homework, |
| 4 | Be informed about tabu search | Lecture, Question-Answer, Discussion, Problem Solving, Project Based Learning, | Homework, |
| 5 | Be informed about ant colony | Lecture, Question-Answer, Discussion, Problem Solving, Project Based Learning, | Homework, |
| 6 | Be informed about hybrid methods | Lecture, Question-Answer, Discussion, Problem Solving, Project Based Learning, | Homework, |
| 7 | Be informed about evolutionary Algorithms | Lecture, Question-Answer, Discussion, Problem Solving, Project Based Learning, | Homework, |
| 8 | Be informed about particle swarm optimization | Lecture, Question-Answer, Discussion, Problem Solving, Project Based Learning, | Homework, |
| 9 | Be informed about constraint handling methods in evolutioanry algortihm | Lecture, Question-Answer, Discussion, Problem Solving, Project Based Learning, | Homework, |
| 10 | Be informed about multi-objective optimization | Lecture, Question-Answer, Discussion, Problem Solving, Project Based Learning, | Homework, |
| 11 | Be informed about current optimization applications in literature | Lecture, Question-Answer, Discussion, Case Study, Self Study, | Homework, |
| 12 | Project implementation is improved | Lecture, Question-Answer, Discussion, Self Study, Problem Solving, Project Based Learning, | Project / Design, |
| Hafta | Ders Konuları | Ön Hazırlık |
|---|---|---|
| 1 | Introduction to adaptive search method | Artificial Intelligence-Introduction to Heuristic optimization algorithms |
| 2 | Simulated annealing Algorithm | Metaheuristics for Hard Optimization: Methods and Case Studies Johann Dréo, Alain Pétrowski , Patrick Siarry, Eric Taillard |
| 3 | Genetic Algorithm | Metaheuristics for Hard Optimization: Methods and Case Studies Johann Dréo, Alain Pétrowski , Patrick Siarry, Eric Taillard |
| 4 | Evolutionary Algorithms | Metaheuristics for Hard Optimization: Methods and Case Studies Johann Dréo, Alain Pétrowski , Patrick Siarry , Eric Taillard, |
| 5 | Tabu Search | Metaheuristics for Hard Optimization: Methods and Case Studies Johann Dréo, Alain Pétrowski , Patrick Siarry , Eric Taillard . |
| 6 | Ant Colony | Metaheuristics for Hard Optimization: Methods and Case Studies Johann Dréo, Alain Pétrowski Patrick Siarry, Eric Taillard |
| 7 | Particle swarm optimization | Metaheuristics for Hard Optimization: Methods and Case Studies Johann Dréo, Alain Pétrowski, Patrick Siarry, Eric Taillard |
| 8 | Hybrid methods | Metaheuristics for Hard Optimization: Methods and Case Studies Johann Dréo, Alain Pétrowski , Patrick Siarry, Eric Taillard |
| 9 | Constraint handling methods in evolutioanry algortihm | Metaheuristics for Hard Optimization: Methods and Case Studies Johann Dréo, Alain Pétrowski, Patrick Siarry , Eric Taillard |
| 10 | Multi-objective optimization | Metaheuristics for Hard Optimization: Methods and Case Studies Johann Dréo, Alain Pétrowski, Patrick Siarry, Eric Taillard |
| 11 | Current optimization applications in literature | |
| 12 | Evaluation and analysis of existing practices | |
| 13 | Project: solving a real problem with a meta-heuristic method | |
| 14 | Evaluating and discussing the developed projects |
| Kaynaklar | |
|---|---|
| Ders Notu | |
| Ders Kaynakları | |
| Sıra | Program Çıktıları | Katkı Düzeyi | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Engineering graduates with sufficient knowledge background on science and engineering subjects of their related area, and who are skillful in implementing theoretical and practical knowledge for modelling and solving engineering problems. | X | |||||
| 2 | Engineering graduates with skills in identifying, describing, formulating and solving complex engineering problems, and thus,deciding and implementing appropriate methods for analyzing and modelling. | X | |||||
| 3 | Engineering graduates with skills in designing a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; for this purpose, skills in implementing modern design methods. | X | |||||
| 4 | Engineering graduates with skills in developing, selecting and implementing modern techniques and tools required for engineering applications as well as with skills in using information technologies effectively. | X | |||||
| 5 | Engineering graduates with skills in designing and conducting experiments, collecting data, analyzing and interpreting the results in order to evaluate engineering problems. | X | |||||
| 6 | Engineering graduates who are able to work within a one discipline or multi-discipline team,as well as who are able to work individually | X | |||||
| 7 | Engineering graduates who are able to effectively communicate orally and officially in Turkish Language as well as who knows at least one foreign language | X | |||||
| 8 | Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology | X | |||||
| 9 | Engineering graduates with well-structured responsibilities in profession and ethics | X | |||||
| 10 | Engineering graduates having knowledge about practices in professional life such as project management, risk management and change management, and who are aware of innovation and sustainable development. | X | |||||
| 11 | Engineering graduates having knowledge about universal and social effects of engineering applications on health, environment and safety, as well as having awareness for juridical consequences of engineering solutions. | ||||||
| Değerlendirme Sistemi | |
|---|---|
| Yarıyıl Çalışmaları | Katkı Oranı |
| 1. Ara Sınav | 25 |
| 1. Proje / Tasarım | 60 |
| 1. Performans Görevi (Uygulama) | 10 |
| 1. Ödev | 5 |
| Toplam | 100 |
| 1. Yıl İçinin Başarıya | 70 |
| 1. Final | 30 |
| Toplam | 100 |
| AKTS - İş Yükü Etkinlik | Sayı | Süre (Saat) | Toplam İş Yükü (Saat) |
|---|---|---|---|
| Course Duration (Including the exam week: 16x Total course hours) | 14 | 3 | 42 |
| Mid-terms | 1 | 5 | 5 |
| Quiz | 1 | 1 | 1 |
| Project / Design | 1 | 16 | 16 |
| Final examination | 1 | 6 | 6 |
| Hours for off-the-classroom study (Pre-study, practice) | 16 | 3 | 48 |
| Assignment | 1 | 5 | 5 |
| Performance Task (Application) | 1 | 3 | 3 |
| Toplam İş Yükü | 126 | ||
| Toplam İş Yükü / 25 (Saat) | 5,04 | ||
| Dersin AKTS Kredisi | 5 | ||