The primary objective of this course is to equip students with the ability to mathematically model and formulate real-world decision-making problems, and to generate numerical solutions for these models. To this end, the course aims to foster a deep understanding of the fundamental assumptions and concepts of Linear Programming. Students will learn various solution techniques, ranging from the graphical method to the Simplex algorithm, enabling them to address optimization problems at both theoretical and practical levels. Furthermore, by modeling and solving special problem types like transportation and assignment problems, and by conducting sensitivity analyses, students will gain the skill to interpret how obtained solutions behave in response to parameter changes. Finally, the course will provide students with practical skills to solve complex optimization problems in a computer environment, offering an opportunity to apply theoretical knowledge to real-world scenarios.

This course aims to equip students with the ability to mathematically model real-world optimization problems using linear programming, solve them with various methods, analyze the solutions, and implement these solutions in a computer environment.