Industrial Engineering (English) | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code: | IE322 | ||||||||
Course Name: | Operations Research II | ||||||||
Course Semester: | Spring | ||||||||
Course Credits: |
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Language of instruction: | EN | ||||||||
Course Requisites: | |||||||||
Does the Course Require Work Experience?: | No | ||||||||
Type of course: | Compulsory | ||||||||
Course Level: |
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Mode of Delivery: | Face to face | ||||||||
Course Coordinator : | Ar.Gör. AHMET SELÇUK YALÇIN | ||||||||
Course Lecturer(s): |
Dr.Öğr.Üyesi GÜNSELİ GÖRÜR |
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Course Assistants: |
Course Objectives: | I. Guiding students in formulating problems and finding appropriate solutions, algorithms or heuristics to solve them. II. Teaching students how to tackle non-linear, integer and dynamic programming problems. |
Course Content: | This course aims to guide students in formulating problems and finding appropriate solutions, algorithms or heuristics to solve them and teach students how to tackle non-linear, integer and dynamic programming problems. |
The students who have succeeded in this course;
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Week | Subject | Related Preparation |
1) | -Modeling Techniques -LP relief forms and graphics solutions | Lecture notes |
2) | -Integer Programming -Cutting plane algorithm -Pure IP solution with the branch and bound technique | Lecture notes |
3) | -Mixed IP solution with branch and bound technique -Branch and bound technique to solving the Knapsack Problem | Lecture notes |
4) | -Modelling and solving IP problems (general review) | Lecture notes |
5) | -Non-Linear programming -Modeling Techniques -Convex and concave functions | Lecture notes |
6) | -Univariate NLP solutions -Multivariable unconstrained NLP solutions -Lagrange multiplier method -Kuhn Tucker conditions | Lecture notes |
7) | Midterm | Exam questions |
8) | -Goal programming -Weighted goal programming -Primary objective programming -Target programming Simplex method | Lecture notes |
9) | -Quadratic Programming -Wolfe method -Removable programming | Lecture notes |
10) | -Dynamic programming concept -DPA solution with the shortest path problem | Lecture notes |
11) | -Solving the Knapsack Problem with DP -Inventory solution with the DP models | Lecture notes |
12) | -Stochastic dynamic programming -Solutions to stochastic inventory model with DP | Lecture notes |
13) | -Project Management: Critical Path Method -Project Management: Program Evaluation and Review Technique | Lecture notes |
14) | General review | Lecture notes |
Course Notes / Textbooks: | Winston, W., (2004) "Operations Research: Applications and Algorithms" 4th Ed., Wadsworth Inc., USA |
References: | I. Taha H.A. (2003) "Operations Research: An Introduction", Pearson Education Inc. II. Taha H.A. (2000) "Yoneylem Arastirmasi", Literatur Yayincilik (cev. Alp Baray ve Sakir Esnaf) III. Winston W.L., Albright S.C. (2001) "Practical Management Science", Duxbury Press, Wadsworth Inc. IV. Render B., Stair R.M. Jr., Hanna M.E. (2003) "Quantitative Analysis for Management", Pearson Education Inc. V. Taylor B.W. III (2002) "Introduction to Management Science", Pearson Education Inc VI. Rardin R.L. (1998) "Optimization in Operations Research", Prentice Hall Inc. VII. Walker R.C. (1999) "Introduction to Mathematical Programming", Prentice Hall Inc. |
Learning Outcomes | 1 |
2 |
3 |
4 |
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Program Outcomes | ||||||||||
1) Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems. | ||||||||||
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose. | ||||||||||
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.) | ||||||||||
4) Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively. | ||||||||||
5) Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems. | ||||||||||
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | ||||||||||
7) Ability to communicate effectively i Turkish, both orally and in writing; knowledge of a minimum of one foreign language. | ||||||||||
8) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | ||||||||||
9) Awareness of professional and ethical responsibility. | ||||||||||
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development. | ||||||||||
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions. |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems. | 5 |
2) | Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose. | 4 |
3) | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.) | 5 |
4) | Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively. | 4 |
5) | Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems. | 1 |
6) | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | |
7) | Ability to communicate effectively i Turkish, both orally and in writing; knowledge of a minimum of one foreign language. | |
8) | Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | 5 |
9) | Awareness of professional and ethical responsibility. | 5 |
10) | Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development. | |
11) | Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions. |
Lesson | |
Problem Solving |
Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing) |
Semester Requirements | Number of Activities | Level of Contribution |
Midterms | 1 | % 50 |
Final | 1 | % 50 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 50 | |
PERCENTAGE OF FINAL WORK | % 50 | |
total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Application | 14 | 3 | 42 |
Study Hours Out of Class | 14 | 8 | 112 |
Midterms | 1 | 2 | 2 |
Final | 1 | 2 | 2 |
Total Workload | 200 |