Course Details

Course Information

Semester	Course Unit Code	Course Unit Title	T+P+L	Credit	Number of ECTS Credits	Last Updated Date
7	IE468	MACHINE SCHEDULING	3+0+0	3	5	26.09.2025

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 Equipping students with essential computer simulation tools Using simulation as a decision-making, comparison or estimation tool
Course Content	This course provides students with a comprehensive overview of machine scheduling in both 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 and question solving sessions.
Prerequisites and co-requisities	( IE212 )
Course Coordinator	None
Name of Lecturers	Asist Prof.Dr. Uğur Satıç ugur.satic@agu.edu.tr
Assistants	None
Work Placement(s)	No

Recommended or Required Reading

Resources	Lecture Slides (available on Canvas)
Course Notes	Michael L. Pinedo, Scheduling Theory, Algorithms, and Systems
Documents	Canvasta
Assignments	Canvasta
Exams	Canvasta

Course Category

Mathematics and Basic Sciences	%50
Field	%100

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	% 30
Yarıl yılSonu Sınavı/Dönem Projesinin Başarı Notuna Katkısı	1	% 30
Final examination	1	% 40
Total	3	% 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	1	30	30
Final Sınavı	1	30	30
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	Formulate appropriate mathematical models for machine scheduling problems
2	Use different machine scheduling algorithms
3	Compare the performance of machine scheduling algorithms.
4	Recognize machine scheduling-related issues and propose solutions.

Weekly Detailed Course Contents

Week	Topics	Study Materials	Materials
1	Syllabus, Deterministik Modellere Giriş	Reading the syllabus	On canvas
2	Single Machine Models		On canvas
3	Advanced Single Machine Models
4	Advanced Single Machine Models
5	Parallel Machine Models (Without Preemptions)
6	Parallel Machine Models (With Preemptions)
7	Flow Shops (Unlimited Storage)
8	Flow Shops (Limited Storage)
9	Midterm Exam
10	Job Shops
11	Job Shops
12	Open Shops
13	Open Shops
14	Open Shops

Contribution of Learning Outcomes to Programme Outcomes

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

https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=78233&lang=en