Tuesday, 15:45 - 16:10 h, Room: MA 141


Panos Parpas
Dimensionality reduction and a maximum principle for multiscale stochastic processes


Weakly connected Markov Processes are often used to capture stochastic dynamics that evolve along different time scales. We show that if the system has sufficient scale separation then a Maximum Principle of reduced order holds. The reduced order Maximum Principle is used to develop a solution algorithm for the optimisation of multiscale processes.


Talk 2 of the invited session Tue.3.MA 141
"Advances in stochastic programming" [...]
Cluster 22
"Stochastic optimization" [...]


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