This course aims to equip students with an understanding of optimization theory and techniques. By the end of the course, students will be able to formulate and solve various optimization problems, interpret the obtained results, and make informed decisions. Students will be equipped with the knowledge and skills to address real-world optimization challenges effectively.

The course content includes topics such as graphical optimization, linear programming, the simplex method, application of the simplex method, duality theory, sensitivity analysis, nonlinear programming, numerical techniques for one-dimensional and unconstrained optimization, discrete optimization, transportation models, and network optimization models.