IE303 Operations Research I

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Course Code Course Title Weekly Hours* ECTS Weekly Class Schedule
T P
IE303 Operations Research I 3 2 6
Prerequisite MATH201 It is a prerequisite to
Lecturer Özge Büyükdağlı Office Hours / Room / Phone
Monday:
13:00-17:00
Tuesday:
15:00-17:00
Wednesday:
15:00-17:00
A F1.9 - 033 957 224
E-mail obuyukdagli@ius.edu.ba
Assistant Assistant E-mail
Course Objectives Operations research (OR) has many applications in science, engineering, economics, and industry. The ability to solve OR problems is crucial for both researchers and practitioners. Being able to solve the real life problems and obtaining the right solution requires understanding and modeling the problem correctly and applying appropriate optimization tools and skills to solve the mathematical model. The goal of this course is to teach you to formulate, analyze, and solve mathematical models that represent real-world problems. We will also discuss how to use spreadsheets and other software packages for solving optimization problems.
Textbook Introduction to Operations Research, 10th edition, by Hillier and Lieberman
Additional Literature
  • Operations Research: An Introduction, 10th edition, 2017, by Hamdy A. Taha, Pearson
Learning Outcomes After successful  completion of the course, the student will be able to:
  1. Formulate a real-world problem as a mathematical programming model
  2. Demonstrate understanding of the theoretical workings of the simplex method for linear programming and perform iterations by hand
  3. Demonstrate understanding of the relationship between a linear program and its dual, including strong duality and complementary slackness
  4. Perform sensitivity analysis to determine the direction and magnitude of change of a model's optimal solution as the data change
  5. Demonstrate understanding of the applications of, basic methods for, and challenges in integer programming
  6. Apply optimality conditions for single- and multiple-variable unconstrained and constrained non-linear models
Teaching Methods Lecture discussion and review questions, class presentations, homework assignments, problem solving in tutorial sessions (every 2 week, 2 hours)
Teaching Method Delivery Face-to-face Teaching Method Delivery Notes
WEEK TOPIC REFERENCE
Week 1 Introduction to the course Syllabus
Week 2 Overview of the Operations Research Modeling Approach Chapter 1-2
Week 3 Introduction to Linear Programming, solving using graphical method, Chapter 3
Week 4 Solving Linear Programming Problems: using spreadsheet Chapter 3
Week 5 Solving Linear Programming Problems: using optimization software Chapter 3
Week 6 Sensitivity analysis
Week 7 Introduction to Integer Programming Chapter 12
Week 8 MIDTERM
Week 9 The Transportation and Assignment Problems Chapter 9
Week 10 Network Optimization Models Chapter 10
Week 11 Dynamic Programming Chapter 12, Taha
Week 12 Inventory Modeling (with Introduction to Supply Chains) Chapter 13, Taha
Week 13 Decision analysis and Games Chapter 15, Taha
Week 14 Project Presentations
Week 15 Review, Preparation for the Final Exam
Assessment Methods and Criteria Evaluation Tool Quantity Weight Alignment with LOs
Final Exam 1 30 1,2,3,4,5,6
Semester Evaluation Components
Project 1 30 1,2,3,4,5,6
Midterm 1 20 1,2,3,4,5,6
Homework 4 20 1,2,3,4,5,6
***     ECTS Credit Calculation     ***
 Activity Hours Weeks Student Workload Hours Activity Hours Weeks Student Workload Hours
Lecture Hours 3 15 45 Project 5 6 30
Home Study 2 15 30 Active Tutorials 2 10 20
Midterm Exam Study 5 2 10 Final Exam Study 5 3 15
        Total Workload Hours = 150
*T= Teaching, P= Practice ECTS Credit = 6
Course Academic Quality Assurance: Semester Student Survey Last Update Date: 15/03/2023
QR Code for https://ecampus.ius.edu.ba/course/math201-linear-algebra

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