Course Details

MACHINE SCHEDULING

IE478

Course Information

Semester	Course Unit Code	Course Unit Title	T+P+L	Credit	Number of ECTS Credits
7	IE478	MACHINE SCHEDULING	3+0+0	3	5

Course Details

Language of Instruction	English
Level of Course Unit	Bachelor's Degree
Department / Program	INDUSTRIAL ENGINEERING
Type of Program	Formal Education
Type of Course Unit	Elective
Course Delivery Method	Face To Face
Objectives of the Course	Grasping the fundamental concepts and principles of scheduling theory Understanding the working principles and mechanisms of various scheduling algorithms Analyzing and comparing these scheduling algorithms using accuracy and performance measures
Course Content	This course provides students with a comprehensive overview of machine scheduling in deterministic systems. Throughout the course, students will explore the fundamentals of scheduling theory, delve into various types of machine scheduling, and examine practical applications in real-world scenarios. By the end of the course, students will have gained a thorough understanding of the principles and practices of machine scheduling, equipping them with the skills necessary to apply these concepts effectively in their professional careers.
Course Methods and Techniques	Face to face lectures
Prerequisites and co-requisities	None
Course Coordinator	None
Name of Lecturers	Asist Prof.Dr. Uğur Satıç
Assistants	None
Work Placement(s)	No

Recommended or Required Reading

Resources	Canvas Michael L. Pinedo, Scheduling Theory, Algorithms, and Systems.
	Michael L. Pinedo, Scheduling Theory, Algorithms, and Systems.
	Canvasta
	Canvasta
	Canvasta

Course Category

Mathematics and Basic Sciences	%50
Engineering	%0
Field	%50

Planned Learning Activities and Teaching Methods

Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria

In-Term Studies	Quantity	Percentage
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı	1	% 10
Yarıl yılSonu Sınavı/Dönem Projesinin Başarı Notuna Katkısı	2	% 50
Final examination	1	% 40
Total	4	% 100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration	Total Work Load
Kişisel Çalışma	14	1	14
Ders dışı çalışma	14	1	14
Yüz Yüze Ders	14	3	42
Ders Dışı Ara Sınav	2	20	40
Final Sınavı	1	20	20
Total Work Load			Number of ECTS Credits 5 130

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:

No	Learning Outcomes
1	Define machine scheduling problems and develop appropriate mathematical models.
2	Select and apply different machine scheduling algorithms.
3	Analyze and compare the performance of machine scheduling algorithms.
4	Identify machine scheduling-related issues and propose solutions.

Weekly Detailed Course Contents

Week	Topics	Study Materials	Materials
1	Syllabus, Introduction to Deterministic Models	Check the Chapter 1 and 2 and bring a question for the lecture.	Chapter 1 and Chapter 2 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
2	Deterministic Single Machine Models	Check the Chapter 3 and bring a question for the lecture.	Chapter 3 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
3	Deterministic Advanced Single Machine Models	Check the Chapter 4 and bring a question for the lecture.	Chapter 4 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
4	Deterministic Parallel Machine Models	Check the Chapter 5 and bring a question for the lecture.	Chapter 5 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
5	Deterministic Parallel Machine Models	Check the Chapter 5 and bring a question for the lecture.	Chapter 5 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
6	Deterministic Flow Shops	Check the Chapter 6 and bring a question for the lecture.	Chapter 6 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
7	Deterministic Flexible Flow Shops	Check the Chapter 6 and bring a question for the lecture.	Chapter 6 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
8	Active Learning Week. Activity: Solving questions from the lecture book before the midterm exam.	Bring a question from the lecture book. You could solve it on the board or we could solve it together.
9	Midterm Exam
10	Determinitic Job Shops	Check the Chapter 7 and bring a question for the lecture.	Chapter 7 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
11	Determinitic Job Shops	Check the Chapter 7 and bring a question for the lecture.	Chapter 7 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
12	Determinitic Open Shops	Check the Chapter 8 and bring a question for the lecture.	Chapter 8 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
13	Determinitic Open Shops	Check the Chapter 8 and bring a question for the lecture.	Chapter 8 of Scheduling Theory, Algorithms, and Systems Lecture notes (On Canvas)
14	Solving questions from the lecture book before the Final exam.	Bring a question from the lecture book. You could solve it on the board or we could solve it together.

Contribution of Learning Outcomes to Programme Outcomes

	P1	P2	P3	P4	P5	P7
C1	3	3	3	1	1
C2	1	3	2	4	1
C3	1	3	1	2	2
C4	2	3	2	1	1	1

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=77403&lang=en

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