GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
HEURISTIC OPTIMIZATION/5431307
Course Title: HEURISTIC OPTIMIZATION
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
At the end of course, the students will learn properties of constructive heuristics and improvement heuristics
single solution-based metaheuristics such as simulated annealing, tabu search, variable neighborhood search, etc. and understand neighborhood structures used in these algorithms
population-based algorithms such genetic algorithms, ant colonies and particle swarm optimization and understand search mechanisms used in these algorithms
performance analysis of heuristics.

 -- MODE OF DELIVERY
  The mode of delivery of this course is face to face
 --WEEKLY SCHEDULE
1. Week  Optimization and Heuristic methods
2. Week  Constructive heuristics and improvement heuristics
3. Week  Representation, neighborhood mechanism and constraint handling
4. Week  Simulated Annealing
5. Week  Simulated Annealing
6. Week  Tabu Search
7. Week  Tabu Search
8. Week  Midterm
9. Week  Other heuristics based on a single-solution search
10. Week  Genetic Algorithms
11. Week  Genetic Algorithms
12. Week  Ant Colonies Optimization
13. Week  Particle Swarm Optimization
14. Week  Performance Analysis of heuristics
15. Week  
16. Week  
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
25
 Assignment
4
15
 Application
1
10
 Projects
1
25
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
75
 Percentage of Final Exam to Total Score  
25
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
14
2
28
 Searching in Internet and Library
5
4
20
 Material Design and Implementation
0
 Report Preparing
4
10
40
 Preparing a Presentation
1
5
5
 Presentation
1
1
1
 Midterm Exam and Preperation for Midterm Exam
2
12
24
 Final Exam and Preperation for Final Exam
2
12
24
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
184
 TOTAL WORKLOAD / 25: 
7.36
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1
2X
3
4X
5X
6X
7X
8
9
10
11
12
 -- NAME OF LECTURER(S)
   (Prof. Dr. Fulya Altıparmak and other relevant faculty members)
 -- WEB SITE(S) OF LECTURER(S)
   (www.gazi.edu.tr/~fulyaal)
 -- EMAIL(S) OF LECTURER(S)
   (fulyaal@gazi.edu.tr)