Quantitative Methods for Systems Analysis

3.0 credits · Graduate

This course will cover quantitative methods for analyzing and solving complex problems. Students will learn both classical and advanced methods, including linear and nonlinear programming, integer programming, heuristic algorithms, simulation, and multi-objective optimization. The course will also cover data-driven optimization to integrate uncertainty in decision-making. This leverages data analytics to enhance the accuracy and reliability of parameter estimation in optimization models. Through a combination of theoretical instruction and hands-on case studies, students will gain the skills to model, analyze, and solve optimization problems in various domains. Emphasis is placed on problem formulation, computational efficiency, and practical implementation using industry-standard tools.