TYPE OF COURSE UNIT | Compulsory Course |
LEVEL OF COURSE UNIT | Bachelor's Degree |
YEAR OF STUDY | 3 |
SEMESTER | Fifth Term (Fall) |
NUMBER OF ECTS CREDITS ALLOCATED | 7 |
NAME OF LECTURER(S) | -
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LEARNING OUTCOMES OF THE COURSE UNIT |
At the end of this course, the students; 1) Understand the basic concepts and principles of the nonlinear programming, integer programming and the dinamic programming 2) are able to understand the conditions of local and global optima in the nonlinear programming 3) are able to understand the optimality conditions of the solution in the integer programming models. 4) can model the problems in the dinamic programming framework 5) can generate the recursive functions in dinamic programming 6) have the ability to solve and interpret the results of nonlinear models with single and multi variables, integer decision models and dinamic programming models
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MODE OF DELIVERY | Face to face |
PRE-REQUISITES OF THE COURSE | Yes(END208) |
RECOMMENDED OPTIONAL PROGRAMME COMPONENT | None |
COURSE DEFINITION | Nonlinear decision models, local and global optima, convexity and quadratic forms. Analytic and numerical solutions of single and multi-variable nonlinear models. Integer programming, branch and bound method. Dynamic programming. Decision making under risk and uncertainty. Game theory. |
COURSE CONTENTS | WEEK | TOPICS |
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1st Week | Project Management: PERT | 2nd Week | Project Management: CPM | 3rd Week | Integer Programming | 4th Week | Integer Programming Models and Examples | 5th Week | Branch and Bound Algorithm | 6th Week | Nonlinear Models and Examples | 7th Week | Convexity, Concavity and Quadratic Forms | 8th Week | Midterm | 9th Week | Analytic and Numerical Solutions to the Single Variable Nonlinear Model | 10th Week | Nonlinear Models with Several Variables | 11th Week | Multi-Stage Decision Models | 12th Week | Dynamic Programming and Examples | 13th Week | Decision Making under Risk and Uncertainty | 14th Week | Decision Making with Multiple Objective |
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RECOMENDED OR REQUIRED READING | Kara, İ. (1986) Doğrusal Olmayan Modeller, Anadolu Üniversitesi Basımevi; Winston, W.L. (1994) Operations Research: Applications and Algorithms, Duxbury Press; Taha, H.A. (1997) Operations Research: An Introduction. |
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS | Lecture,Practice,Presentation |
ASSESSMENT METHODS AND CRITERIA | | Quantity | Percentage(%) |
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Mid-term | 1 | 30 | Quiz | 8 | 30 | Practice | 1 | 15 | Attendance | 1 | 5 | Total(%) | | 80 | Contribution of In-term Studies to Overall Grade(%) | | 80 | Contribution of Final Examination to Overall Grade(%) | | 20 | Total(%) | | 100 |
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ECTS WORKLOAD |
Activities |
Number |
Hours |
Workload |
Midterm exam | 1 | 2 | 2 | Preparation for Quiz | 8 | 4 | 32 | Individual or group work | 14 | 5 | 70 | Preparation for Final exam | 1 | 20 | 20 | Course hours | 14 | 4 | 56 | Preparation for Midterm exam | 1 | 20 | 20 | Laboratory (including preparation) | 1 | 2 | 2 | Final exam | 1 | 2 | 2 | Homework | | | | Total Workload | | | 204 |
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Total Workload / 30 | | | 6,8 |
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ECTS Credits of the Course | | | 7 |
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LANGUAGE OF INSTRUCTION | English |
WORK PLACEMENT(S) | No |
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