EMÜ677 - MILITARY OPERATIONS RESEARCH
Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
---|---|---|---|---|---|---|
MILITARY OPERATIONS RESEARCH | EMÜ677 | Any Semester/Year | 3 | 0 | 3 | 10 |
Prequisites | ||||||
Course language | Turkish | |||||
Course type | Elective | |||||
Mode of Delivery | Face-to-Face | |||||
Learning and teaching strategies | Lecture Discussion Team/Group Work Problem Solving Project Design/Management Other: Lectures, problem solving, discussions, project design/management, individual and group studies | |||||
Instructor (s) | To be determined by the department | |||||
Course objective | The objective of this course is to introduce the operations research methods and theories used in military and defense industries, and to develop students? skills to use software to solve such problems. | |||||
Learning outcomes |
| |||||
Course Content | Introduction to military operations research Decision-making methods in military Linear programming in military Transportation and assignment models in military Integer programming in military Stochastic models in military Multi-criteria decision- making methods in military Game theory in military Heuristic methods in military | |||||
References | Jaiswal, N.K., (2012). ?Military Operations Research: Quantitative Decision Making?. Springer Science+Business Media, LLC. Loerch, A.G., Rainey, L.B. (2007). Methods for Conducting Military Operational Research. Military Operations Research Society |
Course outline weekly
Weeks | Topics |
---|---|
Week 1 | History and importance of military operations research |
Week 2 | Decision-making methods in military |
Week 3 | Linear programming models in military |
Week 4 | Transportation and assignment models in military |
Week 5 | Integer programming in military |
Week 6 | Stochastic models in military |
Week 7 | Queuing models in military |
Week 8 | Inventory models in military |
Week 9 | Midterm exam |
Week 10 | Game theory in military |
Week 11 | Multi-criteria decision-making methods in military |
Week 12 | Network models in military |
Week 13 | Heuristic methods in military |
Week 14 | Project presentations |
Week 15 | Study for the final exam |
Week 16 | Final Exam |
Assesment methods
Course activities | Number | Percentage |
---|---|---|
Attendance | 0 | 0 |
Laboratory | 0 | 0 |
Application | 0 | 0 |
Field activities | 0 | 0 |
Specific practical training | 0 | 0 |
Assignments | 4 | 10 |
Presentation | 1 | 5 |
Project | 1 | 15 |
Seminar | 0 | 0 |
Midterms | 1 | 20 |
Final exam | 1 | 50 |
Total | 100 | |
Percentage of semester activities contributing grade succes | 7 | 50 |
Percentage of final exam contributing grade succes | 1 | 50 |
Total | 100 |
WORKLOAD AND ECTS CALCULATION
Activities | Number | Duration (hour) | Total Work Load |
---|---|---|---|
Course Duration (x14) | 14 | 3 | 42 |
Laboratory | 0 | 0 | 0 |
Application | 0 | 0 | 0 |
Specific practical training | 0 | 0 | 0 |
Field activities | 0 | 0 | 0 |
Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 6 | 84 |
Presentation / Seminar Preparation | 1 | 18 | 18 |
Project | 1 | 50 | 50 |
Homework assignment | 5 | 9 | 45 |
Midterms (Study duration) | 1 | 25 | 25 |
Final Exam (Study duration) | 1 | 36 | 36 |
Total Workload | 37 | 147 | 300 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
D.9. Key Learning Outcomes | Contrubition level* | ||||
---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | |
1. Reach the necessary knowledge and methods in engineering within the scope of advanced industrial engineering studies through scientific research and evaluate knowledge and methods and implement them. | X | ||||
2. Implement advanced analytical methods and modeling techniques to design processes, products and systems in an innovative and original way and improve them | X | ||||
3. Have the competency to plan, manage and monitor processes, products and systems. | X | ||||
4. Evaluate the data obtained from analysis of the processes, products and systems, complete limited or missing data through scientific methods, develop data driven solution approaches. | X | ||||
5. Develop original methods for the efficient integration of the scarce resources such as man, machine, and material, energy, capital and time to the systems and implement these. | X | ||||
6. Effectively utilize computer programming languages, computer software, information and communication technology to solve problems in the field of industrial engineering. | X | ||||
7. Report and present advanced studies, outcomes/results and the evaluations on the design, analysis, planning, monitoring and improvement of processes, products and systems. | X | ||||
8. Are aware of the professional responsibility, describe the technological, economic and environmental effects of the industrial engineering applications, work as an individual independently and as a team member having an understanding of the scientific ethical values, take responsibility and lead the team. | X | ||||
9. Are aware of the up-to-date engineering applications, follow the necessary literature for advanced researches, have the competency to reach knowledge in a foreign language, to quote and implement them. | X |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest