Faculty of Engineering and Natural Sciences · Industrial Engineering (English 30%) · Undergraduate
Course Objective
To teach the concept of modeling and decision making, general methodologies and solution procedures in Operations Research and to provide scientific determination of management policies and activities using this information.
Course Content
Quantitative decision making, modeling philosophy and model building, Formulation and Graphical Solution Method in Linear Programming, Linear Programming applications, Sensitivity Analysis in Graphical Solution, Simplex Method, Revised Simplex Method, Duality and Sensitivity Analysis, Transportation Model, Assignment Model, Transport Model and using Lindo software for solving linear models.
Required Resources
ALADAĞ, Z. (2011) “Yöneylem Araştırması-I” ve “Yöneylem Araştırması-II” Umuttepe Yayınları
APAYDIN, A. (2005) “Optimizasyon” Kılavuz Kitabevi
TAHA, H.A. (2003) “Yöneylem Araştırması” Literatür Yayıncılık (6. Basımdan Çeviri)
Recommended Resources
TECİM, V. (2011) “Yöneylem Araştırması” Lord Matbaacılık
TİMOR, M. (2010) “Yöneylem Araştırması” Türkmen Kitabevi
ÖZKAN, Ş. (2012) “Yöneylem Araştırması” Nobel Yayıncılık
ÖZTÜRK, A. (2005) “Yöneylem Araştırması” Ekin Kitabevi
WINSTON, W.L. (2004) “Operations Research Applications and Algorithms” Thomson Learning (Fourth Edition)
Course Learning Outcomes
- Know the concept of optimization.
- Gains the ability to model and analyze real life problems.
- Gains knowledge about linear models and linear programming.
- Gains the ability to use the methods of finding optimal solutions of mathematical problems.
- It uses some computer software to create, solve and analyze a linear model.
- Can provide solutions and perform analysis for transportation and assignment problems with some special methods.
- Define and model network flows.
Core Area Distribution
Teaching Methods
Assessment & Evaluation
ECTS / Workload
| Activity | Quantity | Duration (h) | Total Workload |
|---|---|---|---|
| Course Duration (Including Exam Week) | 16 | 3 | 48 |
| Out of Class Study Period | 16 | 3 | 48 |
| Midterm | 1 | 10 | 10 |
| Quiz | 3 | 3 | 9 |
| Assignment | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Final | 1 | 25 | 25 |
Course Schedule
| Week | Subject | Preparation |
|---|---|---|
| 1 | Course Introduction and Syllabus Description, Introduction to Quantitative Methods in Decision Making, History of Operations Research, Investigation of Model Concept, Methods in Model Building | Lecture Notes |
| 2 | Establishment of Linear Programming Model, Solution with graphical method | Lecture Notes |
| 3 | Sensitivity analysis in graph solution, solution of major linear programming models | Lecture Notes |
| 4 | Setup of linear programming models, solving with Excel Solver and Lindo | Lecture Notes |
| 5 | Simplex Method | Lecture Notes |
| 6 | Artificial Initial Solution; M Method, Two Stage Method | Lecture Notes |
| 7 | Special Situations Encountered in Simplex Method Applications | Lecture Notes |
| 8 | Midterm Exam | Midterm Exam |
| 9 | Duality and Sensitivity Analysis | Lecture Notes |
| 10 | Dual Simplex Method, Primal-Dual Calculations | Lecture Notes |
| 11 | Transportation Models, Transportation Algorithm | Lecture Notes |
| 12 | Assignment Model, Transportation Model | Lecture Notes |
| 13 | Network Models, Minimum Spanning Tree | Lecture Notes |
| 14 | Shortest path problem, Maximum Flow Model | Lecture Notes |
| 15 | Minimum Cost Capacity Flow Problem, CPM and PERT | Lecture Notes |
| 16 | Final Exam | Final Exam |