Fundamental concepts, solution techniques, modeling approaches, and applications of decision analytics.
Problem and project-based approaches:
Commonly used methods of optimization, simulation and decision analysis techniques for prescriptive analytics in business. Explore linear programming, network optimization, integer linear programming, goal programming, multiple objective optimization, nonlinear programming, metaheuristic algorithms, stochastic simulation, queuing modeling, decision analysis, and Markov decision processes. Develop a contextual understanding of techniques useful for managerial decision support. Implement decision-analytic techniques using a state-of-the-art analytical modeling platform.