MS&E Dynamic 
Programming and Stochastic Control



What is MS&E 351

Markov population decision chains in discrete and continuous time. Risk posture. Present value, Cesaro-overtaking and Cesaro-geometric-overtaking optimality. Optimal stopping. Successive approximation, policy improvement, and linear programming methods. Team decisions and stochastic programs; quadratic costs and certainty equivalents. Maximum principle. Controlled diffusions. Examples from supply, overbooking, options, investment, queues, reliability, quality, capacity, transportation. MATLAB is used. Prerequisites: Mathematics 113, 115; Markov chains; linear programming.