COURSE INTRODUCTION AND APPLICATION INFORMATION

se.cs.ieu.edu.tr

Course Name

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
	Fall/Spring

Prerequisites

ISE 203

To succeed (To get a grade of at least DD)

Course Language

Course Type

Elective

Course Level

Mode of Delivery

Teaching Methods and Techniques of the Course

Course Coordinator

Course Lecturer(s)

Assistant(s)

Course Objectives
Learning Outcomes	The students who succeeded in this course; Will be able to list the basic heuristic methods for optimization Will be able to compare and contrast these methods with classical optimization methods Will be able to list basic meta-heuristic methods for optimization Will be able to adapt these heuristic methods especially to Industrial Systems Engineering problems Will be able to improve these heuristic methods adapted to Industrial Systems Engineering problems Will be able to implement Improve these heuristic methods adapted to Industrial Systems Engineering problems
Course Description

Course Category	Core Courses
	Major Area Courses
	Supportive Courses
	Media and Managment Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Required Materials
1	Reminder for Optimization	Reading: Textbook (Michalewicz) introduction Ch 1
2	Introduction to complexity and heuristics	Lecture notes/slides provided
3	Simulated Annealing	Lecture notes/ slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 8
4	Particle Swarm Optimization	Lecture notes/slides provided
5	Genetic Algorithms and Evolutionary Strategies 1	Lecture notes/slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 3
6	Genetic Algorithms and Evolutionary Strategies 1	Lecture notes/slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 3
7	MIDTERM
8	Ant Colony Optimization	Lecture notes/slides provided, Reading: Handbook of Metaheuristics Ch 9
9	Tabu Search	Lecture notes/slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 2
10	BAYRAM
11	GRASP	Lecture notes/slides provided Handbook of Metaheuristics Ch 8
12	Scatter Search	Lecture notes/slides provided Handbook of Metaheuristics Ch 1
13	Local Search 1	Lecture notes/slides provided Handbook of Metaheuristics Ch 11
14	Local Search 2 Neighbourhoods, VNS	Lecture notes/slides provided Reading: Handbook of MetaheuristicsCh 6
15	Review of Final	Lecture notes/slides provided
16	Review of the Semester

Course Notes/Textbooks	Textbook:Zbigniew Michalewicz, David B. Fogel “How to Solve It: Modern Heuristics
Suggested Readings/Materials	"Handbook of Metaheuristics" edt by: Glover F.,, Kochenberger G.A., Kluwer, 2003 and Lecture PowerPoint slides

EVALUATION SYSTEM

Semester Activities	Number	Weigthing
Participation		5
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	5	20
Presentation / Jury
Project	1	35
Seminar / Workshop
Oral Exam
Midterm	1	20
Final Exam	1	20
Total

Weighting of Semester Activities on the Final Grade		80
Weighting of End-of-Semester Activities on the Final Grade		20
Total

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: 16 x total hours)	16
Study Hours Out of Class	15	2
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	5	2
Presentation / Jury
Project	1	14
Seminar / Workshop
Oral Exam
Midterms	1	8
Final Exams	1	10
		Total	120

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	Program Competencies/Outcomes	* Contribution Level
#	Program Competencies/Outcomes	1	2	3	4	5
1	Be able to define problems in real life by identifying functional and nonfunctional requirements that the software is to execute
2	Be able to design and analyze software at component, subsystem, and software architecture level
3	Be able to develop software by coding, verifying, doing unit testing and debugging
4	Be able to verify software by testing its behaviour, execution conditions, and expected results
5	Be able to maintain software due to working environment changes, new user demands and the emergence of software errors that occur during operation
6	Be able to monitor and control changes in the software, the integration of software with other software systems, and plan to release software versions systematically
7	To have knowledge in the area of software requirements understanding, process planning, output specification, resource planning, risk management and quality planning
8	Be able to identify, evaluate, measure and manage changes in software development by applying software engineering processes
9	Be able to use various tools and methods to do the software requirements, design, development, testing and maintenance
10	To have knowledge of basic quality metrics, software life cycle processes, software quality, quality model characteristics, and be able to use them to develop, verify and test software
11	To have knowledge in other disciplines that have common boundaries with software engineering such as computer engineering, management, mathematics, project management, quality management, software ergonomics and systems engineering
12	Be able to grasp software engineering culture and concept of ethics, and have the basic information of applying them in the software engineering		X
13	Be able to use a foreign language to follow related field publications and communicate with colleagues				X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest