Computer Engineering (English)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

General course introduction information

Course Code:

IE423

Course Name:

Heuristic Methods in Optimization

Course Semester:

Fall

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Compulsory

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi MEHMET TEVFİK ÇOBANOĞLU

Course Lecturer(s):

Dr.Öğr.Üyesi GÜNSELİ GÖRÜR

Course Assistants:

Course Objective and Content

Course Objectives:

The aim of this course is to provide the students with the knowledge of mathematical modeling and the operation of heuristic algorithms. Topics include basic intuitive structures (greedy, improvement, construction); simulated annealing, tabu search, genetic algorithm, ant colony and similar metasoric algorithms. The basic information about the intuitions in the courses will be provided as a note. Students are expected to make various applications related to the course. In addition, as a project assignment, they are expected to write a program to solve a problem with a suitable heuristic method and to measure the performance of this program.

Course Content:

Reminder of operations research
Introduction to complexity and intuition
Annealing Simulation
Particle Swarm Optimization
Genetic Algorithm and Evolutionary Strategies 1
Genetic Algorithm and Evolutionary Strategies 2
Ant Colony Optimization
Tabu Search
Tabu Search
GRASP
Scatter Search
Local Research 1
Local Research 2 Neighborhoods

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Ability to solve problems with metacognitive methods.
2 - Skills
Cognitive - Practical
1) Basic heuristic methods can be coded for basic problems
3 - Competences
Communication and Social Competence
Learning Competence
1) Developing calculations that enable heuristic methods to run faster.
Field Specific Competence
1) Developing heuristic methods for problems similar to basic problems.
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	Reminder of operations research
2)	Introduction to complexity and intuition
3)	Annealing Simulation
4)	Particle Swarm Optimization
5)	Genetic Algorithm and Evolutionary Strategies 1
6)	Genetic Algorithm and Evolutionary Strategies 2
7)	Ant Colony Optimization
8)	Tabu Search
9)	Tabu Search
10)	MIDTERM
11)	GRASP
12)	Scatter Search
13)	Local Research 1
14)	Local Research 2 Neighborhoods
15)	VNS
16)	FINAL EXAMS

Sources

Course Notes / Textbooks:	Ragsdale,C.T. (2007) Spreadsheet Modeling Decision Analysis Timor, Mehpare(2010) Yöneylem Araştırması
References:	Ragsdale,C.T. (2007) Spreadsheet Modeling Decision Analysis Timor, Mehpare(2010) Yöneylem Araştırması

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3	4
Program Outcomes
1) Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2) The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
3) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5) Ability to design experiments, conduct experiments, collect data, analyze and interpret results for examination of engineering problems.
6) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7) Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge.
8) Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Professional and ethical responsibility.
10) Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
11) Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2)	The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
3)	The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4)	Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5)	Ability to design experiments, conduct experiments, collect data, analyze and interpret results for examination of engineering problems.
6)	The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7)	Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge.
8)	Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9)	Professional and ethical responsibility.
10)	Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
11)	Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions.

Learning Activity and Teaching Methods

Lesson
Reading
Homework

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework
Presentation

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	1	% 40
Final	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	1	1	1
Homework Assignments	7	1	7
Quizzes	5	5	25
Midterms	5	1	5
Total Workload			38