Mixed-Integer Programming (MIP) is a fundamental technique for solving complex real-world optimization problems in logistics, scheduling, and resource allocation. However, these problems are combinatorially hard, requiring specialized solvers to find optimal solutions efficiently. This talk introduces Pyomo, a Python-based modeling language, and HiGHS, a state-of-the-art open-source solver. We will first explore the class of problems that MIP can solve, discuss why they are computationally challenging, and then explain how modern solvers like HiGHS tackle these challenges. Using conference scheduling as a real-world example, we demonstrate how Pyomo and HiGHS work together to model and solve an optimization problem. Attendees will leave with a clear understanding of how to leverage these tools for scientific and industrial optimization tasks.