Course Information

Course Name	Turkish	Sezgisel Eniyileme
	English	Heuristic Optimization
Course Code	END 557E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Gülgün Kayakutlu
Course Objectives		1. To introduce variety of heuristic methods with mathematics and field of application. 2. Modeling heuristic algorithms in optimization 3. To allow modeling and implementation of one method in an optimization field.
Course Description		Business problems like machine scheduling, portfolio selection, resource allocation and supply chain network design are considered NP-complete problems. Though classical optimization methods are used in modeling there is no known efficient way to locate a solution in the first place. Decision makers are happy with finding a near-optimal solution using Heuristic approaches. This course will be presenting the most recent meta-heuristic techniques using combinatorial and continuous samples. Simulated Annealing, Tabu Search, Genetic Algorithm, Ant Colony, Swarm Intelligence will be focused, but an overview of other methods will be given. Attendees will gain knowledge of where and how to use heuristic methods in addition to reading comparisons with classical algorithms in selected papers.
Course Outcomes		M.Sc. students who successfully pass this course gain knowledge, skills and proficiency in the following subjects 1. Necessity of Heuristics, 2. Mathematics and application fields of Search algorithms and Simple Heuristics, 3. Mathematics and application fields Genetic Algorithms, 4. Mathematics and application fields Ant Colony and Swarm Intelligence, 5. Modeling optimization problems using Heuristics, 6. Overview of other Meta-Heuristic Methods 7. Programming and application of one method on an optimization problem.
Pre-requisite(s)
Required Facilities
Other
Textbook		El-G. Talbi, Metaheuristics: From Design to Implementatin, John Wiley & Sons, New York, 2009.
Other References		C.R. Reeves. Modern Heuristic Techniques for Combinatorial Problems, John Wiley & Sons, New York, 1993. V. J. Rayward-Smith (Editor), I. H. Osman (Editor), C. R. Reeves (Editor), G. D. Smith (Editor). Modern Heuristic Search Methods, John Wiley & Sons, New York, 1996. M. Gen, R. Cheng, Genetic Algorithms and Engineering Design, John Wiley & Sons, New York, 1997. M. Clerc, Particle Swarm Optimization, John Wiley & Sons, New York,2006. Franz Rothlauf, Design of Modern Heuristics: Principles and Application, Springer Berlin, 2011.

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