This course introduces learners to quantitative techniques for optimizing complex decision-making processes. Topics include linear and nonlinear programming, integer and dynamic programming, queuing theory, simulation modeling, and multi-criteria decision analysis (MCDA). Emphasizing practical applications, students will gain skills to model real-world problems, analyze uncertainties, and implement solutions across various industries such as logistics, manufacturing, and finance.