Information Package / Course Catalogue
Optimization Algorithms and Applications
Course Code: MIS521
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 7
Objectives of the Course

This course is a survey of the newer, most common adaptive search methods. This undergraduate course with emphasis on self exploration and research. There will be homework assignments, a quiz, an exam and a project. The homework assignments and the project should be done individually. The project can synthesize multiple techniques or be an in depth exploration of one technique using problems and applications are of the student’s choice

Course Content

The areas of focus will be simulated annealing, genetic algorithms, evolutionary strategies, tabu search, ant colony methods and particle swarm optimization. Other methods will be briefly covered. Both combinatorial and continuous optimization problems will be considered, with emphasis on combinatorics. The main techniques will be introduced, discussed critically and variations presented.

Name of Lecturer(s)
Learning Outcomes
1.Gains the knowledge and skills of problem solving by using linear optimization algorithms.
2.Gains the knowledge and skills of problem solving by using nonlinear optimization algorithms.
3.Gains the knowledge and skills of problem solving using discrete optimization algorithms.
4.Learn about flock intelligence
5.Learn about genetic basis algorithms
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Optimiztion
Week 2 - Theoretical
Simulated Annealing
Week 3 - Theoretical
Introduction to Evolutionary Computation
Week 4 - Theoretical
Evolutionary Strategies
Week 5 - Theoretical
Quadratic Assignment problem-Short Term Memory
Week 6 - Theoretical
Optimization and Machine learning
Week 7 - Theoretical
Long term memory-Tabu Search
Week 8 - Intermediate Exam
MIDTERM
Week 9 - Theoretical
Ant Colony Optimization
Week 10 - Theoretical
Particle Swarm Optimization
Week 11 - Theoretical
Current Heuristic Applications in Literature
Week 12 - Theoretical
Implementing one Optimization Method for a real problem as Project
Week 13 - Theoretical
Evaluation of Suggested Project
Week 14 - Theoretical
Comparison of The Heuristics According to Project Results
Week 15 - Final Exam
FINAL
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory161364
Assignment18513
Project101010
Individual Work161364
Midterm Examination11910
Final Examination151520
TOTAL WORKLOAD (hours)181
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
OÇ-1
4
5
5
5
5
5
5
5
OÇ-2
4
4
4
4
4
5
5
5
5
4
OÇ-3
4
5
5
5
5
5
4
4
4
OÇ-4
5
5
5
5
5
5
5
5
5
OÇ-5
4
4
4
5
5
5
5
5
5
5
Adnan Menderes University - Information Package / Course Catalogue