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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
ISY 606MULTI-PURPOSE GENETIC ALGORITHMS3 + 02nd Semester7,5

COURSE DESCRIPTION
Course Level Doctorate Degree
Course Type Elective
Course Objective Angles events One of these methods have been developed more flexible and high performance genetic algorithm, which is difficult with this method of solving the problems of convenience, to a different approach under uncertainty: a scientific approach to alternative ideas to demonstrate concepts such as genetic algorithm
Course Content Introduction to genetic algorithms, stochastic search methods, heuristic approaches, the traditional optimization techniques, objective of the optimization; an optimization methods as genetic algorithms, difference from other optimization techniques, multi-purpose optimization, weighted sum approach, fixed weight random weight approach and the simple genetic algorithm, theoretical basis of genetic algorithms, fuzzy multi-purpose genetic algorithms, basic theorems, the application area of genetic algorithms .
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Learns the Concept of Genetic algorithm
2Analatik the thought of ability to comprehend
3Allows optimization problems using genetic algorithm
4Classifies the methods of learning
5Provides a different approach to uncertainty

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07
LO 0014425  4
LO 0024425  4
LO 0034425  4
LO 0044425  4
LO 0054425  4
Sub Total20201025  20
Contribution4425004

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
Assignments5525
Mid-terms12020
Final examination12222
Presentation / Seminar Preparation31030
Total Work Load

ECTS Credit of the Course






195

7,5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2016-2017 Spring1İRFAN ERTUĞRUL
Details 2015-2016 Spring1İRFAN ERTUĞRUL
Details 2014-2015 Spring1İRFAN ERTUĞRUL
Details 2013-2014 Spring1İRFAN ERTUĞRUL


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
ISY 606 MULTI-PURPOSE GENETIC ALGORITHMS 3 + 0 1 Turkish 2016-2017 Spring
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Prof. Dr. İRFAN ERTUĞRUL iertugrul@pau.edu.tr İİBF A0117 %70
Goals Angles events One of these methods have been developed more flexible and high performance genetic algorithm, which is difficult with this method of solving the problems of convenience, to a different approach under uncertainty: a scientific approach to alternative ideas to demonstrate concepts such as genetic algorithm
Content Introduction to genetic algorithms, stochastic search methods, heuristic approaches, the traditional optimization techniques, objective of the optimization; an optimization methods as genetic algorithms, difference from other optimization techniques, multi-purpose optimization, weighted sum approach, fixed weight random weight approach and the simple genetic algorithm, theoretical basis of genetic algorithms, fuzzy multi-purpose genetic algorithms, basic theorems, the application area of genetic algorithms .
Topics
WeeksTopics
1
2
3
4
5
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7
8
9
10
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13
14
Materials
Materials are not specified.
Resources
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes