Systems Optimization: Methods and Models

0.5 credit · Graduate

Management science approaches in modeling systems for decision-making under certainty and uncertainty. Linear programming, network flows problems and applications, discrete optimization models, heuristics and metaheuristics, dynamic programming, nonlinear programming, simulation. Links between theory and application will be illustrated through case studies and applied modeling.