This course provides a rigorous foundation in the analytical methodologies of Operations Research, focusing on structured optimization and stochastic models. Designed for students seeking to master data-driven decision-making, the curriculum covers five core domains critical to modern industrial engineering, logistics, and management sciences. Students will begin by learning how to formulate and solve classical transportation algorithms and assignment problems. The course then transitions to network analysis techniques, where learners master critical path methods, evaluation techniques, and routing algorithms. A thorough exploration of linear programming follows, introducing the structural mechanics of modeling and graphical visualization. Moving into probabilistic systems, the course provides deep insights into deterministic and stochastic inventory models, balancing holding and shortage costs under physical storage constraints. Finally, the curriculum examines queuing systems, analyzing waiting line mechanics using Poisson distributions, birth-death frameworks, and complex service formulas. By balancing core theoretical mechanics with extensive exercise problems from foundational literature like Hamdy Taha’s Operations Research, this course equips students with the exact mathematical toolsets needed to resolve operational bottlenecks and drive strategic efficiency.