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| BILL5170 | Smart Optimization Algorithms | 3+0+0 | ECTS:7.5 | | Year / Semester | Fall Semester | | Level of Course | Second Cycle | | Status | Elective | | Department | DEPARTMENT of COMPUTER ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | -- | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The course intends to teach the students for computational problem solving techniques from the fields of computational Intelligence, Biologically Inspired Computation, and Metaheuristics Optimization. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | Understand what optimization. | 1,2,3,4 | 1,3 | | PO - 2 : | Gain knowledge on Artificial Intelligence and Algorithms. | 1,2,3,4,13 | 1,3 | | PO - 3 : | Compare various problem solving algorithms and technique-specific guidelines. | 1,2,5,13 | 1,3 | | PO - 4 : | Implement state-of-the-art algorithms to address business or scientific needs. | 2,3,4,5,11,12 | 1,3 | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| Introduction to Intelligence Algorithm and Metaheuristic Optimization, Stochastic Algorithms, Evolutionary Algorithms, Physical Algoritmhs, Probabilistic Algorithms, Swarm Optimization Algorithms, Immune Algorithms, Programming Paradigms, Testing Algorithms, Problem Solving Strategies |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction to Intelligence Algorithm and Metaheuristic Optimization | | | Week 2 | Stochastic Algorithms : Random Search, Stochastic Hill Climbing | | | Week 3 | Stochastic Algorithms : Local Search | | | Week 4 | Stochastic Algorithms : Tabu Search | | | Week 5 | Evolutionary Algorithms: Genetic Algorithm, Genetic Programming, | | | Week 6 | Evolutionary Algorithms: Differential Evolution, Evolutinary programming | | | Week 7 | Evolutionary Algorithms: Learning Classifier System, | | | Week 8 | Physical Algoritmhs: Simulated Annealing, Cultural Algorithm, | | | Week 9 | Mid-term exam | | | Week 10 | Probabilistic Algorithms: Population-Based Incremental Learning, | | | Week 11 | Probabilistic Algorithms: Bayesian Optimization Algorithm, Cross-Entropy Method | | | Week 12 | Swarm Optimization Algorithms: Particle Swarm Optimization, Ant Colony System, Bees Algorithm | | | Week 13 | Swarm Optimization Algorithms: Optimization Algorithm, Bat Algorithm | | | Week 14 | Immune Algorithms: Selection Algorithms, Artificial Immune Recognition System, | | | Week 15 | Programming Paradigms, Testing Algorithms, Problem Solving Strategies | | | Week 16 | Final Exam | | | |
| 1 | Clever Algorithms: Nature-Inspired Programming Recipes, Jason Brownlee, Creative Commons, 2011(438 sayfa), ISBN: 978-1-4467-8506-5 | | | 2 | Swarm Intelligence and Bio-Inspired Computation Theory and Applications, Xin-She Yang, Zhihua Cui, Renbin Xiao, Amir Hossein Gandomi, and Mehmet Karamanoglu, Elsevier, First edition 2013(420 sayfa) | | | 3 | Theory and New Applications of Swarm Intelligence, Edited by Rafael Parpinelli and Heitor S. Lopes, InTech, 2012(204 sayfa), ISBN 978-953-51-0364-6 | | | 4 | Yapay Zeka Optimizasyon Algoritmaları, Derviş Karaboğa, Nobel Yayın Dağıtım, 2004 (199 sayfa). | | | |
| 1 | Nature-inspired Metaheuristic Algorithms, Xin-She Yang, Luniver Press, 2010 (160 sayfa). | | | 2 | Engineering Optimization: An Introduction with Metaheuristic Applications, Xin-She Yang, Wiley Press, 2010 (347 pages). | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 2 | 20 | | Presentation | 14 | | 1 | 15 | | Homework/Assignment/Term-paper | 13 | | 1 | 25 | | End-of-term exam | 16 | | 2 | 40 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 7 | 14 | 98 | | Laboratuar çalışması | 0 | 0 | 0 | | Arasınav için hazırlık | 6 | 2 | 12 | | Arasınav | 2 | 1 | 2 | | Uygulama | 0 | 0 | 0 | | Klinik Uygulama | 0 | 0 | 0 | | Ödev | 3 | 10 | 30 | | Proje | 3 | 9 | 27 | | Kısa sınav | 0 | 0 | 0 | | Dönem sonu sınavı için hazırlık | 6 | 2 | 12 | | Dönem sonu sınavı | 2 | 1 | 2 | | Diğer 1 | 0 | 0 | 0 | | Diğer 2 | 0 | 0 | 0 | | Total work load | | | 225 |
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