Course Details

LINEAR PROGRAMMING

IE513

Return to Classes
Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
1IE513LINEAR PROGRAMMING3+0+037,5

Course Details
Language of Instruction English
Level of Course Unit Master's Degree
Department / Program INDUSTRIAL ENGINEERING
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course To recognize the concept of duality and its importance in proving the optimality of a solution.
To equip the students with the capability of developing and coding algorithms to solve different types of models including linear, network, integer, and non-linear programming models.
To model and solve real-world problems in homework and project assignments.
Course Content This course is a continuation of the course IE211 Mathematical Modeling in which the process of mathematical modeling, the development of models, and the coding and solution of the models by off-the-shelf software are emphasized. In this course, the solution techniques and algorithms for different types of problems, e.g., simplex, dual simplex, network simplex, branch-and-bound algorithms and decomposition techniques, are introduced. Modeling and solving real-world problems are also emphasized in this course. Homework and project assignments will enhance students’ modeling and problem solving abilities in practice.
Course Methods and Techniques Lectures following the course material, student participation in problem-solving sessions, group work within the class, assignments, quizzes, midterm exams, final exams, and an ongoing real-life project throughout the semester.
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Asist Prof.Dr. Betül Kayışoğlu betul.kayisoglu@agu.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Operations Research: Applications and Algorithms by Wayne L. Winston, 4th Edition, Thomson Brooks/Cole, 2004.
Will be published on CANVAS.
Will be published on Canvas
Will be published on Canvas
Will be published on Canvas

Course Category
Mathematics and Basic Sciences %15
Engineering %60
Engineering Design %25
Social Sciences %0
Education %0
Science %0
Health %0
Field %0

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
Veri yok

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Ev Ödevi 3 5 15
Sunum 2 3 6
Proje 1 60 60
Kısa Sınav 5 1 5
Rapor 1 20 20
Ders dışı çalışma 14 3 42
Yüz Yüze Ders 14 4 56
Final Sınavı 1 3 3
Total Work Load   Number of ECTS Credits 7 207

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Formulate decision problems as linear, integer, nonlinear, network flow, and multi-objective models and implement them using optimization software.
2 Differentiate between convex and non-convex optimization problems and learn the general search technique in solving optimization problems.
3 Solve linear programming problems by means of the graphical approach, primal and dual simplex methods and be able to decide under which conditions a method is applicable.
4 Solve integer linear programming problems by means of branch and bound and branch and cut methods.
5 Examine network flow models and solution algorithms for these models
6 Design a team project to solve a real-world problem and share the results of a real-world problem related team project (written and orally) with peers in a meaningful and professional manner.


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction N/A Lecture Slides
2 Simplex Algorithm N/A Lecture Slides
3 Simplex Algorithm N/A Lecture Slides
4 Simplex Algorithm N/A Lecture Slides
5 Dual Simplex Algorithm N/A Lecture Slides
6 Solving Network Flow Models N/A Lecture Slides
7 Project Progress Presentation/Midterm N/A Lecture Slides
8 Simplex Algorithm, Dual Simplex Algorithm N/A Lecture Slides
9 Solving Network Flow Models, Transportation Problem, Network Simplex Algorithms N/A Lecture Slides
10 Ford- Fulkerson Method, Dijkstra’s Algorithm, Floyd-Warshall Method N/A Lecture Slides
11 Introduction to Solving Integer Programming Models N/A Lecture Slides
12 Branch-and-Bound Method & Branch-and-Cut Algorithm, Decomposition Methods N/A Lecture Slides
13 Solving Non-Linear Programming Models, Decision Analysis Models N/A Lecture Slides
14 Project Final Presentations N/A Lecture Slides


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
All 2 2 1 1 1 1 1 1 1 1 1 1
C1 3 4
C2
C3 1
C4 1
C5 3 1
C6 4 5 3 5 3 2 2 1 1 1 1 4

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=77278&lang=en
Return to Classes