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•           Information on Degree Programmes

COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Mathematical Programming * ENM   333 5 3 3 4

 Prerequisites and co-requisites Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Asst.Prof.Dr. Melik KOYUNCU
Instructors
 Dr. Öğr. Üyesi MELİK KOYUNCU 1. Öğretim Grup:A

Assistants
Goals
To develop the operations researck skills and knowledge to delve into the mathematical modelling techniques
Content
To review the mathematical modelling techniques, Introduction to integer programming , The application area of integer programming, Solution methodology of integer programming ( branch and boun algorithm , additive algortihm) , Dynamic programming and its applications , The solution methodology of Dynamic progrramming , Introduction to Network models, The shortest path problem , Maximum flow problem and its applications, Minumum spanning tree problem and its applications, The network models related algorithm , Solving the some manufacturing problems by netwok models , Multiobjective optimization techniques, Introduction to goal programming , The solution methodology of goal programming

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Has sufficient background on topics related to mathematics, physical sciences and industrial engineering.
X
2
Gains ability to use the acquired theoretical knowledge on basic sciences and industrial engineering for describing, formulating and solving an industrial engineering problem, and to choose appropriate analytical and modeling methods.
X
3
Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems .
X
4
Gains ability to choose and apply methods and tools for industrial engineering applications.
X
5
Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions.
X
6
Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team.
X
7
Can access information and to search/use databases and other sources for information gathering.
X
8
Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously.
X
9
Can use computer software in industrial engineering along with information and communication technologies.
X
10
Can use oral and written communication efficiently.
X
11
Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession.
X
12
Has a conscious understanding of professional and ethical responsibilities.
X
13
Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice.
X
14
Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering.
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 To review the mathematical modelling techniques Standart lecture tools (Teaching on board and application)
2 Introduction to integer programming Standart lecture tools (Teaching on board and application)
3 The application areas of integer programming Standart lecture tools (Teaching on board and application)
4 Solution methodology of integer programming ( branch and bound algorithm , additive algortihm) Standart lecture tools (Teaching on board and application)
5 Dynamic programming and its applications Standart lecture tools (Teaching on board and application)
6 The solution methodology of Dynamic programming Standart lecture tools (Teaching on board and application)
7 Midterm Exam Classical Midternl Exam
8 Introduction to Network models Standart lecture tools (Teaching on board and application)
9 The shortest path problem Standart lecture tools (Teaching on board and application)
10 Maximum flow problem and its applications Standart lecture tools (Teaching on board and application)
11 Minumum spanning tree problem and its applications Standart lecture tools (Teaching on board and application)
12 The network models related algorithm Standart lecture tools (Teaching on board and application)
13 Solving the some manufacturing problems by netwok models Standart lecture tools (Teaching on board and application)
14 Multiobjective optimization techniques Standart lecture tools (Teaching on board and application)
15 Introduction to goal programming Standart lecture tools (Teaching on board and application)
16-17 Final Exam Classical Final Exam