PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
INS 534	GENETIC ALGORITHMS	3 + 0	1st Semester	7,5

COURSE DESCRIPTION

Course Level	Master's Degree
Course Type	Elective
Course Objective	The main purpose of this course is to teach the main mathematical background of the Genetic algorithms and to investigate possible application in civil engineering problems.
Course Content	A gentle introduction to genetic algorithms, mathematical foundations, Computer implementation of a genetic algorithm, some applications of genetic algorithms, advanced operators and techniques in genetic search
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	Will be able to know basic principles of genetic algorithms
2	Problem formulation with GA can be learned
3	Problem solution with GA can be learned
4	How civil engineering problems can be solved with GA
5	Will be able to evaluate GA solutions

COURSE'S CONTRIBUTION TO PROGRAM

	PO 01	PO 02	PO 03	PO 04	PO 05	PO 06	PO 07	PO 08	PO 09	PO 10	PO 11
LO 001	4		3	2		1	2			4
LO 002	4		5	5		1	2			4
LO 003	4		5	5		1	2			4
LO 004	4		5	5		1	2			4
LO 005	4		5	5		1	2			4
Sub Total	20		23	22		5	10			20
Contribution	4	0	5	4	0	1	2	0	0	4	0

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	14	3	42
Assignments	2	30	60
Mid-terms	1	25	25
Final examination	1	26	26
Total Work Load ECTS Credit of the Course			195 7,5

COURSE DETAILS

Select Year

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
INS 534	GENETIC ALGORITHMS	3 + 0	1	Turkish	2023-2024 Spring

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Prof. Dr. HALİM CEYLAN	halimc@pau.edu.tr		MUH B0115	%

Goals		The main purpose of this course is to teach the main mathematical background of the Genetic algorithms and to investigate possible application in civil engineering problems.
Content		A gentle introduction to genetic algorithms, mathematical foundations, Computer implementation of a genetic algorithm, some applications of genetic algorithms, advanced operators and techniques in genetic search

Topics

Weeks	Topics
1	What are genetic algorithms
2	The Goals of optimization
3	How are genetic algorithms differenet from traditional methods?
4	A simple genetic algorithm
5	Genetic algorithms at work
6	Who shall live and who shall die? The fundamental theorem
7	The building block hypothesis
8	Examination
9	Practice
10	Computer implementation of a genetic algorithm
11	Data structures, reproduction, crossover, and mutation
12	Data structures, reproduction, crossover, and mutation
13	Fitness scaling
14	Advanced operators and techniques in genetic search

Materials

Materials are not specified.

Resources

Resources	Resources Language
Goldberg, d (1989) .Genetic algorithms, in serach, optimization &machine learning	Türkçe

Course Assessment

Assesment Methods	Percentage (%)	Assesment Methods Title
Final Exam	50	Final Exam
Midterm Exam	50	Midterm Exam

L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

Prospective Student