IE251 LINEAR PROGRAMMING
| Course Code: | 5680251 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 5.0 |
| Department: | Industrial Engineering |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Assoc.Prof.Dr. MUSTAFA KEMAL TURAL |
| Offered Semester: | Fall Semesters. |
Course Objectives
At the end of the course the students will:
1. have an understanding of the general principles of linear programming.
2. acquire the skills to formulate and build linear programming models, understand how to solve linear programming problems and how to make sensitivity analysis.
3. understand the basic concepts and solution approaches to multi-criteria decision making problems.
4. develop an understanding of the conflicts among different parties and be able to analyze the interactions among decision-makers.
5. learn to solve large scale linear programs using software and interpret software output.
Course Content
History and methodology of operational research. Introduction to linear programming and graphical solution. Linear programming models and interpretation of solutions. Simplex method, sensitivity analysis and duality. Multi-criteria decision making. Game Theory.
Course Learning Outcomes
1.1. describe steps of model building process.
1.2. define assumptions of linear programming models.
1.3. identify application areas of linear programming.
2.1. define parameters, decision variables, objectives and constraints.
2.2. develop linear programming models.
2.3. solve linear programming models and make sensitivity analysis using the graphical method.
2.4. solve linear programming models using the simplex method and perform sensitivity analysis.
2.5. identify the relation between the primal and the dual problems.
3.1. identify efficient solutions.
3.2. use goal programming to solve multi-criteria decision making problems.
3.3. identify relevant costs in a decision making problem.
3.4. select among alternative courses of actions.
4.1. find the optimal strategies and the values of two-person constant-sum games.
4.2. find the equilibrium points for two-person nonconstant-sum games.
4.3. use the core and the Shapley value for n-person games.
5.1. solve linear programming models using software.
5.2. perform sensitivity analysis using software output.
5.3. select among alternative courses of actions.
Program Outcomes Matrix
| Contribution | |||||
| # | Program Outcomes | No | Yes | ||
| 1 | An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | ✔ | |||
| 2 | An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | ✔ | |||
| 3 | An ability to communicate effectively with a range of audiences | ✔ | |||
| 4 | An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | ✔ | |||
| 5 | An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | ✔ | |||
| 6 | An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | ✔ | |||
| 7 | An ability to acquire and apply new knowledge as needed, using appropriate learning strategies | ✔ | |||
| 8 | An ability to design, analyze, operate, and improve integrated systems that produce and/or supply products and/or services in an effective, efficient, sustainable, and socially responsible manner | ✔ | |||
| 9 | An ability to apply critical reason and systems thinking in problem solving and systems design | ✔ | |||
| 10 | An ability to use scientific methods and tools (such as mathematical models, statistical methods and techniques) necessary for industrial engineering practice | ✔ | |||