Computer Programming
Course Details
KTO KARATAY UNIVERSITY
Trade and Industry Vocational School
Programme of Computer Programming
Course Details
Trade and Industry Vocational School
Programme of Computer Programming
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 03831196 | Operations Research | 2 | Autumn | 3 | 2+1+0 | 5 | 5 |
| Course Type | Elective |
| Course Cycle | Associate (Short Cycle) (TQF-HE: Level 5 / QF-EHEA: Short Cycle / EQF-LLL: Level 5) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | Lect. Özlem AKARÇAY PERVİN |
| Instructor(s) | Lect. Özlem AKARÇAY PERVİN |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Lect. Özlem AKARÇAY PERVİN | TSMYO-T213 | [email protected] | 7916 |
Course Content
Introduction to numerical methods in decision making; Formulation and graphical method in Linear programming; The applications of Linear programming; Sensitivity Analysis in Graphical solution; Simplex Method in Linear Programming; Special situation in Simplex Method; Duality and Sensitivity Analysis in Linear Programming; Transportation models in Linear Programming; Assignment Model in Linear Programming; theory and solution procedure of Integer Linear Programming
Objectives of the Course
To teach common methodology and solution procedure of modeling and decision making concept in operations research and to find management politics and activities using these information.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | X |
| Specialization / Field Courses | X |
| Support Courses | X |
| Transferable Skills Courses | X |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P4 | Effectively uses information technologies (software, programs, animations, etc.) related to her/his profession. | 4 |
| P8 | Has awareness of career management and lifelong learning. | 4 |
| P5 | Has the ability to independently evaluate professional problems and issues with an analytical and critical approach and propose solutions. | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Ability to use software suitable for current mathematical modeling and optimization methods | P.4.2 | 1 |
| O2 | Determines the skills required to solve problems and develops methods. | P.8.1 | 1 |
| O3 | Applies the methods developed to solve problems effectively and efficiently. | P.8.2 | 1 |
| O4 | Knows effective research and solution techniques to identify problems. | P.8.3 | 1 |
| O5 | Can develop solutions to mathematical problems | P.5.6 | 1 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Introduction to numerical methods in decision making; The Art and Science of Operation Research; The research of decision making and model concept; The steps in Operations Research Study |
| 2 | Formulation and graphical method in Linear programming; Construction of A mathematical model; Formulating linear programming model of a simple case and finding solution graphically and graphical solution procedure |
| 3 | Special Problems in Constructing Lines at graphical solution procedure; Linear Programming applications and problem Formulations; Production planning; Product mix Selection; Assigning Personnel; Portfolio Selection and other of Linear Programming Applications |
| 4 | Sensitivity Analysis in Graphic Solution; Sensitivity Analysis for right-hand value; The solution for right-hand change; The change in objective function coefficients |
| 5 | The Algebraic Solution in Linear Programming (Simplex Method); The standard form of a Linear Programming and basic solution; Determining Basic Solution |
| 6 | Introduction to Simplex Method and Computational Details of The Simplex Algorithm; Artificial Starting Solution; The M-Technique; The Two-Phase Technique |
| 7 | The Special Problems in Simplex Method Applications; Degeneration; Alternative Optimal Solution; Bounded solution and infeasible solution |
| 8 | Duality and Sensitivity Analysis in Linear Programming; Description of Dual Problem; The Relationship between Optimal Primal and Dual Solutions; The Economic Explanation of Duality |
| 9 | Dual Simplex Method; Primal-Dual Calculations; Sensitivity Analysis; Changes Affecting Feasibility; The Changes Affecting Optimality |
| 10 | Dual Simplex Method; Primal-Dual Calculations; Sensitivity Analysis; Changes Affecting Feasibility; The Changes Affecting Optimality |
| 11 | Transportation Model in Linear Programming; The Description of Transportation Model; Formulating Transportation Model as Linear Model; The Description of Transportation Algorithm; The Methods of determine beginning solution |
| 12 | The Optimal solution of Transportation Model and Describing Method of Multipliers with Simplex Method; The description of Assignment Problem and Assignment Model; The Solution of Assignment Model; The Transshipment Model |
| 13 | The Optimal solution of Transportation Model and Describing Method of Multipliers with Simplex Method; The description of Assignment Problem and Assignment Model; The Solution of Assignment Model; The Transshipment Model |
Textbook or Material
| Resources | Operations Research, Hamdy TAHA, 6th Ed. |
| Operations Research, Hamdy TAHA, 6th Ed. | |
| Operations Research, Hamdy TAHA, 6th Ed. |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Field Study | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Seminar | - | - |
| Quiz | - | - |
| Listening | - | - |
| Midterms | 1 | 40 (%) |
| Final Exam | 1 | 60 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 3 | 42 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 4 | 56 |
| Midterms | 1 | 10 | 10 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 14 | 1 | 14 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 20 | 20 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 142 | ||
| Total Work Load / 30 | 4,73 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P4 | P5 | P8 |
|---|---|---|---|---|
| O1 | Ability to use software suitable for current mathematical modeling and optimization methods | 4 | - | - |
| O2 | Can develop solutions to mathematical problems | - | 5 | - |
| O3 | Determines the skills required to solve problems and develops methods. | - | - | 3 |
| O4 | Applies the methods developed to solve problems effectively and efficiently. | - | - | - |
| O5 | Knows effective research and solution techniques to identify problems. | - | - | - |