Course Information

Course Name	Turkish	Sezgisel Arama
	English	Heuristic Optimization
Course Code	END 457E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Seda Yanık Özbay
Course Objectives		The difficulty level of many real world problems in business are considered to be NP-Complete. Utilizing conventional optimization techniques in this type of problems is either computationally expensive or do not yield to a result. However, utilizing Heuristic Search algorithms, a near-optimum solution can be found in a short amount of time. This course firstly provides a detailed introduction to Heuristic Search algorithms. Simulated Annealing, Tabu Search, Genetic Algorithm, Ant Colony and Swarm Intelligence will be in the focus, but an overview of other methods will also be given. Attendees will gain knowledge of where and how to use heuristic methods in addition to reading about comparisons with classical algorithms in selected papers.
Course Description		The difficulty level of many real world problems in business are considered to be NP-Complete. Utilizing conventional optimization techniques in this type of problems is either computationally expensive or do not yield to a result. However, utilizing Heuristic Search algorithms, a near-optimum solution can be found in a short amount of time. This course firstly provides a detailed introduction to Heuristic Search algorithms. Simulated Annealing, Tabu Search, Genetic Algorithm, Ant Colony and Swarm Intelligence will be in the focus, but an overview of other methods will also be given. Attendees will gain knowledge of where and how to use heuristic methods in addition to reading about comparisons with classical algorithms in selected papers.
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