IE 355 | Course Introduction and Application Information - Department of Industrial Engineering

Course Name

Art of Mathematical Modelling

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
IE 355	Fall/Spring	2	2	3	6

Prerequisites

IE 252 To succeed (To get a grade of at least DD)

Course Language

English

Course Type

Elective

Course Level

First Cycle

Mode of Delivery

-

Teaching Methods and Techniques of the Course

Problem Solving
Lecture / Presentation

National Occupation Classification

-

Course Coordinator

Yrd. Doç. Dr. Kamil Erkan Kabak

Course Lecturer(s)

Yrd. Doç. Dr. Kamil Erkan Kabak

Assistant(s)

-

Course Objectives

The aim of this course is to teach students building mathematical models and heuristic solution algorithms of real-life problems and to enable them solving the complex problems encountered in business.

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	explain existing mathematical models
2	develop conceptual models for decision making problems
3	transform conceptual models to mathematical model formulations
4	develop heuristic solution algorithms for decision making problems
5	develop mathematical models and heuristic solution algorithms for essential problems in industrial system engineering
6	code mathematical models and heuristic solution algorithms in IBM ILOG OPL Development Studio

Course Description

Topics of this course include developing mathematical models and heuristic solution algorithms for essential Industrial Systems Engineering problems. During the course, IBM ILOG OPL Development Studio will be used to code and solve mathematical models and heuristic algorithms.

Related Sustainable Development Goals

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

Week	Subjects	Related Preparation	Learning Outcome
1	Introduction to Mathematical Modeling and OPL	IBM ILOG CPLEX OPTIMIZATION STUDIO (OPL) Documentation version 16, A Short Introduction to OPL
2	Building a Basic Mathematical Model: indexed decision variables, parameters and constraints	Ch 3, Winston, W. L., Operations Research: Applications and Algorithms, Duxbury Press
3	Building a Basic Mathematical Model: a production planning problem model	Ch 3, Winston, W. L., Operations Research: Applications and Algorithms, Duxbury Press
4	Building Linear Programming Models I : Workforce Planning model	Ch 3, Winston, W. L., Operations Research: Applications and Algorithms, Duxbury Press
5	Building Linear Programming Models II: CPM model	Ch 8, Winston, W. L., Operations Research: Applications and Algorithms, Duxbury Press
6	Building Linear Programming Models III: Supply planning model	Ch 9, Hillier, F. S., and Lieberman, G. J., Introduction to Operations Research, Tentth Edition, 2015 Mc Graw-Hill
7	Linearizing Logical Forms with Binary Variables	Ch 6, Sierksma, G. Linear and Integer Programming Theory and Practice, Marcel Dekker Inc. Second Edition
8	Building Integer Programming Models: Modeling integer programming models with conditional decisions	Ch 6-7, Sierksma, G. Linear and Integer Programming Theory and Practice, Marcel Dekker Inc. Second Edition
9	Building Integer Programming Models: set packing, covering and partitioning problems	Ch 6-7, Sierksma, G. Linear and Integer Programming Theory and Practice, Marcel Dekker Inc. Second Edition Ch 19, Winston, W. L., Operations Research: Applications and Algorithms, Duxbury Press
10	Algorithm development and programming with ILOG OPL	IBM ILOG CPLEX OPTIMIZATION STUDIO (OPL) Documentation version 16
11	Quadratic Assignment Problem and Model Formulation	Ch 11, Rardin, R. L., Optimization in Operations Research, 1998, Prentice-Hall
12	Traveling Salesman Problem and Model Formulation, Heuristic Solution Algorithms	Ch 9, Winston, W. L., Operations Research: Applications and Algorithms, Duxbury Press
13	Cutting Stock Problem and Model Formulation	Ch 10, Winston, W. L., Operations Research: Applications and Algorithms, Duxbury Press
14	Project Presentations
15	Review of the semester
16	Final Exam

Course Notes/Textbooks

Operations Research: Applications and Algorithms, Wayne L. Winston, Duxbury Press, ISBN 0-534 20971-8.,

Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman, Tenth Edition, 2015 Mc Graw-Hill, ISBN: 978-007-126767-0

Linear and Integer Programming Theory and Practice, Gerard Sierksma, Marcel Dekker Inc., Second Edition, ISBN 978-0824706739

Optimization in Operations Research, Ronald L.Rardin, Prentice Hall, ISBN : 0-02-398415-5

Suggested Readings/Materials

Logic and Integer Programming, H. Paul Williams, Springer, ISBN 978-0387922799

M. L. Pinedo, Scheduling: Theory, Algorithms, and Systems, 2005, Springer, ISBN 978-0387789347

Semester Activities	Number	Weigthing	LO 1	LO 2	LO 3	LO 4	LO 5	LO 6
Participation	1	20
Laboratory / Application	1	20
Field Work
Quizzes / Studio Critiques	1	15
Portfolio
Homework / Assignments
Presentation / Jury	1	15
Project	1	30
Seminar / Workshop
Oral Exams
Midterm
Final Exam
Total

Weighting of Semester Activities on the Final Grade	4	70
Weighting of End-of-Semester Activities on the Final Grade	1	30
Total

Semester Activities	Number	Duration (Hours)	Workload
Theoretical Course Hours (Including exam week: 16 x total hours)	16	2	32
Laboratory / Application Hours (Including exam week: '.16.' x total hours)	16	2	32
Study Hours Out of Class	14	4	56
Field Work			0
Quizzes / Studio Critiques	1	20	20
Portfolio			0
Homework / Assignments			0
Presentation / Jury	1	10	10
Project	1	30	30
Seminar / Workshop			0
Oral Exam			0
Midterms			0
Final Exam			0
		Total	180

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	To have adequate knowledge in Mathematics, Science and Industrial Engineering; to be able to use theoretical and applied information in these areas to model and solve Industrial Engineering problems.		-	-	X	-	-
2	To be able to identify, formulate and solve complex Industrial Engineering problems by using state-of-the-art methods, techniques and equipment; to be able to select and apply proper analysis and modeling methods for this purpose.		-	-	-	-	X
3	To be able to analyze a complex system, process, device or product, and to design with realistic limitations to meet the requirements using modern design techniques.		-	X	-	-	-
4	To be able to choose and use the required modern techniques and tools for Industrial Engineering applications; to be able to use information technologies efficiently.		-	X	-	-	-
5	To be able to design and do simulation and/or experiment, collect and analyze data and interpret the results for investigating Industrial Engineering problems and Industrial Engineering related research areas.		-	X	-	-	-
6	To be able to work efficiently in Industrial Engineering disciplinary and multidisciplinary teams; to be able to work individually.		X	-	-	-	-
7	To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively; to be able to give and receive clear and comprehensible instructions		-	-	-	-	-
8	To have knowledge about contemporary issues and the global and societal effects of Industrial Engineering practices on health, environment, and safety; to be aware of the legal consequences of Industrial Engineering solutions.		-	-	-	-	-
9	To be aware of professional and ethical responsibility; to have knowledge of the standards used in Industrial Engineering practice.		-	-	-	-	-
10	To have knowledge about business life practices such as project management, risk management, and change management; to be aware of entrepreneurship and innovation; to have knowledge about sustainable development.		-	-	-	-	-
11	To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language.		-	-	-	-	-
12	To be able to speak a second foreign at a medium level of fluency efficiently.		-	-	-	-	-
13	To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Industrial Engineering.		X	-	-	-	-