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

 

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

 

Abstract:
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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