FACULTY OF ENGINEERING

Department of Computer Engineering

IE 355 | Course Introduction and Application Information

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
Service Course
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Problem Solving
Lecture / Presentation
Course Coordinator
Course Lecturer(s)
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 The students who succeeded in this course;
  • explain existing mathematical models
  • develop conceptual models for decision making problems
  • transform conceptual models to mathematical model formulations
  • develop heuristic solution algorithms for decision making problems
  • develop mathematical models and heuristic solution algorithms for essential problems in industrial system engineering
  • 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.

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
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

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
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

ECTS / WORKLOAD TABLE

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

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Computer Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

2

To be able to identify, define, formulate, and solve complex Computer Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Computer Engineering applications; to be able to use information technologies effectively.

5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Computer Engineering research topics.

6

To be able to work efficiently in Computer Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

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 global and social impact of Computer Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Computer Engineering solutions.

9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.

10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Computer Engineering, and to be able to communicate with colleagues in a foreign language. ("European Language Portfolio Global Scale", Level B1)

12

To be able to speak a second foreign language 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 Computer Engineering.

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

 


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