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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
ISY 658META-HEURISTIC METHODS 3 + 02nd Semester7,5

COURSE DESCRIPTION
Course Level Doctorate Degree
Course Type Elective
Course Objective The aim of this course is to examine meta-heuristic methods through theoretical and real-life applications. In this course, meta-heuristics methods and their applications will be presented.
Course Content In this course, Various meta-heuristic methods such as Genetic Algorithm, Tabu Search, Simulated Annealing, Ant Colony Optimization, Particle Swarm Optimization, Variable Neighborhood Search and Scatter Search are defined. In addition, these methods will be discussed in real life problems.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1To aid the students to learn the basic principles of meta-heuristic methods.
2To enable students to solve complex optimization problems with meta-heuristic method.
3To enable students to make research on meta-heuristic methods.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07
LO 001       
LO 002       
LO 003       
Sub Total       
Contribution0000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14456
Assignments14342
Mid-terms11010
Final examination11515
Report / Project21530
Total Work Load

ECTS Credit of the Course






195

7,5
COURSE DETAILS
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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes