Mechanical & Industrial Engrg 697SB - ST-Simulation-Based Optimizatn

This class will look at optimization problems related to stochastic systems for which the analytical form of the objective function are not known or are too complex to formulate. But the value of the function can be evaluated at specific points of the decision variables through simulation, and the problem can be solved using numerical optimization techniques. We will learn multiple algorithms for solving such problems. We will look at both static systems (parametric optimization) and dynamic systems (control optimization). Topics will include: response surfaces, neural networks, simultaneous perturbation, simulated annealing, dynamic programming, and reinforcement learning.

M&I-ENG 620 & 684 Undergraduates who are interested in this course and have taken M&I ENG 379 and M&I ENG 380 should contact the instructor.