11111

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 203To 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)
Assistant(s)
Course Objectives
Learning Outcomes The students who succeeded in this course;
  • Will be able to read and interpret existing mathematical models
  • Will be able to develop conceptual models for decision making problems
  • Will be able to transform conceptual models to mathematical model formulations
  • Will be able to develop heuristic solution algorithms for decision making problems
  • Will be able to develop mathematical models and heuristic solution algorithms for essential problems in industrial system engineering
  • Will be able to code mathematical models and heuristic solution algorithms in IBM ILOG OPL Development Studio
Course Description

 



Course Category

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

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Introduction to Mathematical Modeling and OPL Lecture notes
2 Building Linear Programming Models I : Workforce Planning Lecture notes
3 Building Linear Programming Models II: Supply planning and CPM models Lecture notes
4 Linearizing Logical Forms with Binary Variables, Lecture notes
5 Building Integer Programming Models: Modeling integer programming models with conditional decisions, set packing, covering and partitioning problems Lecture notes
6 Algorithm development and programming with ILOG OPL Lecture notes
7 Quadratic Assignment Problem Model Formulations and Heuristic Solution Algorithms Lecture notes
8 Traveling Salesman Problem Model Formulations and Heuristic Solution Algorithms Lecture notes
9 Industrial Applications of Integer Programming I : Lot Sizing and Scheduling Models, Wagner Whitin Algorithm Lecture notes
10 Industrial Applications of Integer Programming II : Assembly Line Balancing , Dedicated Storage System Models and Heuristic Solution Algorithms Lecture notes
11 Industrial Applications of Integer Programming III : Modeling Machine Scheduling Problems I : Single Machine and Job Shop Scheduling Problems Lecture notes
12 Industrial Applications of Integer Programming IV : Modeling Machine Scheduling Problems II : Single Machine and Job Shop Scheduling Problems with sequence dependent setup times Lecture notes
13 Industrial Applications of Integer Programming V : Modeling Machine Scheduling Problems III : Heuristic solution algorithms and constraint programming models to solve single machine and job shop scheduling problems Lecture notes
14 Project Presentations, Reading journal papers
15 General Review, Discussion and Evaluation
16 Review
Course Notes/Textbooks Model Building in Mathematical Programming, Fourth ed., H. Paul Williams, WILEY.
Suggested Readings/Materials Lecture PowerPoint slides, Reading Handouts, Articles from journals, Optimization in Operations Research, Ronald L.Rardin, Prentice Hall, ISBN : 0-02-398415-5, Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman, Ninth Edition, 2010 Mc Graw-Hill, ISBN: 978-007-126767-0 , Operations Research: Applications and Algorithms, Wayne L. Winston, Duxbury Press, ISBN 0-534 20971-8., Linear and Integer Programming Theory and Practice, Gerard Sierksma, Marcel Dekker Inc., Second Edition, ISBN 978-0824706739, Optimization Modeling A Practical Approach, Ruhul A. Sarker, Charles S. Newton, CRC Press, 2008, ISBN 978-1420043105, Applied Integer Programming, Modeling and Solution. Der-San Chen, Robert G. Batson, Yu Dang, Wiley, 2010. ISBN 978-0-470-37306-4, Logic and Integer Programming, H. Paul Williams, Springer, ISBN 978-0387922799, M. L. Pinedo, Scheduling: Theory, Algorithms, and Systems, 2005, Springer, ISBN 978-0387789347, IBM ILOG CPLEX OPTIMIZATION STUDIO (OPL) Documentation.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
1
5
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
1
15
Presentation / Jury
Project
1
10
Seminar / Workshop
Oral Exam
Midterm
1
30
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
60
Weighting of End-of-Semester Activities on the Final Grade
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
2
32
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
2
Study Hours Out of Class
15
1
Field Work
Quizzes / Studio Critiques
2
2
Portfolio
Homework / Assignments
1
1
Presentation / Jury
Project
1
15
Seminar / Workshop
Oral Exam
Midterms
1
8
Final Exams
1
10
    Total
117

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
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,
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

 

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