COURSE INTRODUCTION AND APPLICATION INFORMATION

dm.ieu.edu.tr

Course Name

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

Prerequisites

ISE 204

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)

Prof. Dr. Beno KURYEL

Assistant(s)

Course Objectives
Learning Outcomes	The students who succeeded in this course; Will be able to describe the limitations of classical optimization methods Will be able to model production management and industrial systems engineering field problems using these methods Will be able to model production management and industrial systems engineering field problems using dynamic programming Will be able to model production management and industrial systems engineering field problems using hybrid optimization methods Will be able to solve these production management and industrial systems engineering field problems models' using appropriate software
Course Description

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

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Required Materials
1	Fundamentals of Optimization Review	Lecture Notes
2	Dissasembly Problems, - Introduction, definitions, classification	Lecture Notes
3	Disassembly specific examples definitions, disassembly planning - Presentation	Lecture Notes
4	Disassembly Planning - Presentation	Lecture Notes
5	Disassembly Scheduling 1/2 - Presentation	Lecture Notes
6	Mini test 1	Lecture Notes
7	Disassembly Scheduling - Presentation	Lecture Notes
8	Mini Test 2	Lecture Notes
9	Disassembly Heuristics - Presentations
10	Advanced Planning and Scheduing - Lot Sizing and Scheduling - Presentation	Lecture Notes
11	Lot Sizing and Scheduling - Presentation	Lecture Notes
12	Mini Test 3 / Lot Sizing and Scheduling - Presentation	Lecture Notes
13	Lot Sizing and Scheduling - Presentation	Lecture Notes
14	Mini Test 4 / Lot Sizing and Scheduling - Presentation	Lecture Notes
15	Review and Presentations	Lecture Notes
16	Review of the Semester

Course Notes/Textbooks
Suggested Readings/Materials

EVALUATION SYSTEM

Semester Activities	Number	Weigthing
Participation		20
Laboratory / Application
Field Work
Quizzes / Studio Critiques	4	20
Portfolio
Homework / Assignments	2	10
Presentation / Jury	2	20
Project
Seminar / Workshop
Oral Exam
Midterm
Final Exam	1	30
Total

Weighting of Semester Activities on the Final Grade		65
Weighting of End-of-Semester Activities on the Final Grade		35
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
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	2	45
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms	1	12
Final Exams	1	15
		Total	165

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	Program Competencies/Outcomes	* Contribution Level
#	Program Competencies/Outcomes	1	2	3	4	5
1	To have a grasp of basic mathematics, applied mathematics and theories and applications of statistics.
2	To be able to use theoretical and applied knowledge acquired in the advanced fields of mathematics and statistics,
3	To be able to define and analyze problems and to find solutions based on scientific methods,
4	To be able to apply mathematics and statistics in real life with interdisciplinary approach and to discover their potentials,					X
5	To be able to acquire necessary information and to make modeling in any field that mathematics is used and to improve herself/himself,					X
6	To be able to criticize and renew her/his own models and solutions,			X
7	To be able to tell theoretical and technical information easily to both experts in detail and nonexperts in basic and comprehensible way,
8	To be able to use international resources in English and in a second foreign language from the European Language Portfolio (at the level of B1) effectively and to keep knowledge up-to-date, to communicate comfortably with colleagues from Turkey and other countries, to follow periodic literature,
9	To be familiar with computer programs used in the fields of mathematics and statistics and to be able to use at least one of them effectively at the European Computer Driving Licence Advanced Level,			X
10	To be able to behave in accordance with social, scientific and ethical values in each step of the projects involved and to be able to introduce and apply projects in terms of civic engagement,
11	To be able to evaluate all processes effectively and to have enough awareness about quality management by being conscious and having intellectual background in the universal sense,
12	By having a way of abstract thinking, to be able to connect concrete events and to transfer solutions, to be able to design experiments, collect data, and analyze results by scientific methods and to interfere,
13	To be able to continue lifelong learning by renewing the knowledge, the abilities and the compentencies which have been developed during the program, and being conscious about lifelong learning,
14	To be able to adapt and transfer the knowledge gained in the areas of mathematics and statistics to the level of secondary school,
15	To be able to conduct a research either as an individual or as a team member, and to be effective in each related step of the project, to take role in the decision process, to plan and manage the project by using time effectively.

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