Basic Information

Course Code:

IE 2002

Course Name:

Operations Research II

Language of Instruction:

English

Course Type:

Class

Course Level:

Bachelor

ECTS:

6.00

Instructor:

Dr. Öğr. Üyesi Kamer ÖZGÜN

Course Objectives

This course covers fundamental optimization methods with a focus on linear programming, network models, and integer linear programming. It emphasizes both the approaches used to obtain optimal solutions and the understanding of how these methods work.

Course Content

The Linear Programming Problem, matrix notation, the Extreme Point Theorem, basic solutions, the simplex method, artificial variables, duality, the duality theorem, sensitivity analysis, integer programming problems, cutting plane methods, branch and bound method, other optimization methods.

Prerequisites / Corequisites

MATH 1004, IE 2001

Course Books / Materials / Recommended Resources

Course notes, presentations, and application files are provided through the Learning Management System (LMS). Relevant chapters from standard textbooks (e.g., Winston, W. L. & Goldberg, J. B., Operations Research: Applications and Algorithms, and Taha, H. A., Operations Research: An Introduction) are used as reference materials in this course.

Learning Outcomes

Code	Description
LO1	Apply classical optimization methods to linear programming problems
LO2	Solve linear programming problems using the simplex method.
LO3	Analyze linear programming problems using duality theory.
LO4	Apply and interpret sensitivity and dual analysis for optimal solutions.
LO5	Solve integer programming problems using branch-and-bound and cutting-plane methods and compare the results.

Weekly Course Content

Week	Content
1	Review of Linear Programming and Problem Formulation (LO1)
2	Simplex Method – Basic Concepts (LO2)
3	Simplex Method – Iterations (LO2)
4	Artificial Variables and Advanced Simplex Methods (LO2)
5	Duality Theory – Fundamentals (LO3)
6	Duality and Dual Simplex Method (LO3)
7	Sensitivity Analysis (Graphical and Algebraic) (LO4)
8	Midterm Exam
9	Introduction to Integer Programming (LO5)
10	Branch and Bound Method – I (LO5)
11	Branch and Bound Method – II (LO5)
12	Cutting Plane Methods (LO5)
13	Applications Using Optimization Software (LO1, LO5)
14	Integrated Problems and Model Analysis (LO3, LO4, LO5)
15	Review and Final Exam Preparation (LO1–LO5)

Workload Calculation

Activity	Count	Duration (Hours)	Total
Attendance	14	2.00	28.00
Practice	14	2.00	28.00
Pre-Class Individual Study	14	2.00	28.00
Post-Prectice Individual Study	14	3.00	42.00
Midterm Exam/Preparation	1	15.00	15.00
Final Exam/Preparation	1	20.00	20.00
Homework	3	6.00	18.00
Total Workload (Hours)			179
ECTS Credit (Workload / 25)			6

Assessment

#	Assessment Type	Contribution (%)
1	Midterm Exam	%30
2	Homework	%30
3	Final Exam	%40
TOTAL		%100

PO - LO Matrix

PO \ LO	LO1	LO2	LO3	LO4	LO5
PO-1
PO-2
PO-3
PO-4
PO-5
PO-6
PO-7
PO-8
PO-9
PO-10
PO-11

1

Low Contribution

2

Medium Contribution

3

High Contribution

Teaching and Learning Methods

#	Method Name	Description	Tools
1	Lecture (expository teaching), interactive discussion	Listening and taking notes.	Standard classroom technologies, multimedia tools (projector, computer, digital presentations)
2	Homework	Solving and analyzing homework questions using a computer and Excel.	Computer

Academic Integrity and Artificial Intelligence

Students are expected to comply with academic integrity rules. AI tools may be used only for learning purposes; submitting AI-generated content as one’s own work is prohibited. Students must be able to understand and explain their solutions. The use of AI tools during exams is not allowed.