1. FIRST CYCLE - BACHELOR'S DEGREE
  2. FACULTY OF ENGINEERING
  3. COMPUTER ENGINEERING DEPARTMENT
  4. 253 Computer Engineering
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
CENG 415EVOLUTIONARY COMPUTATION3 + 07th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Elective
Course Objective Purpose of this course is to provide understanding of basic theories and methods related to evolutionary computation. Students will arrive solution of complex problems due to methods given during course. Students will understand the methods from basic to complex ones and can use these methods to solve different engineering problems.
Course Content Basic approaches: Genetic algorithms, Genetic programming, evolutionary strategies. Traditional Genetic algorithm, mathematical bases, sema theory, coding, computation of correctness. Genetic operators: cross over, mutation, producing, selection methods. Advanced operators: diploid structures, parallel Genetic algorithms. Application areas. Current research topics.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Understanding of basic optimization concepts
2Understanding of Genetic Algorithm operators
3Understanding of Hybrid Genetic Algorithm
4Understanding of Several Genetic Algorithm
5Understanding of Alternative Algorithms

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
LO 00151155 1 3   
LO 00251155 1 3   
LO 00351155 1 3   
LO 00451155 1 3   
LO 00551155 1 3   
Sub Total25552525 5 15   
Contribution511550103000

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)10550
Mid-terms11313
Final examination12525
Total Work Load

ECTS Credit of the Course





130

5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2023-2024 Fall1ŞEVKET UMUT ÇAKIR


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
CENG 415 EVOLUTIONARY COMPUTATION 3 + 0 1 Turkish 2023-2024 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Lecturer ŞEVKET UMUT ÇAKIR sucakir@pau.edu.tr MUH A0435 %
Goals Purpose of this course is to provide understanding of basic theories and methods related to evolutionary computation. Students will arrive solution of complex problems due to methods given during course. Students will understand the methods from basic to complex ones and can use these methods to solve different engineering problems.
Content Basic approaches: Genetic algorithms, Genetic programming, evolutionary strategies. Traditional Genetic algorithm, mathematical bases, sema theory, coding, computation of correctness. Genetic operators: cross over, mutation, producing, selection methods. Advanced operators: diploid structures, parallel Genetic algorithms. Application areas. Current research topics.
Topics
WeeksTopics
1 Basic approaches in optimization
2 Genetic Algorithms
3 Genetic Programming
4 Evolutionary Strategies
5 Binary Genetic Algorithm
6 Continues Genetic Algorithm
7 Genetic Coding
8 Genetic Cross Over and Mutation
9 Genetic producing and selection
10 Genetic advanced operators
11 Hybrid Genetic Algorithms
12 Parallel Genetic Algorithms
13 Application of Genetic Algorithm
14 Current research topics
Materials
Materials are not specified.
Resources
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam60Final Exam
Midterm Exam40Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes