Learning Objectives :
This subject is about probabilistic and stochastic optimization problems. Modelling and methods studied primarily are Decision Making, Stochastic Dynamic Programming, Markov chain, Markov Processes Birth-Death, Queuing Systems, Theory of Games
Competencies :
1. Students are able to formulate problems that are probabilistic/ stochastic formulation into the network analysis, dynamic program, markov analysis, queuing theory, game theory
2. Students are able to solve the problem of decision making under probabilistic/ stochastic conditions
3. Students are able to solve the problems programa dynamic stochastics
4. Students are able to understand the process and markov transition matrix
5. Students are able to find a solution to the problem queue
6. Students are able to perform stochastic simulation problems
Subject :
Decision Making, Stochastic Dynamic Programming, Markov Chains, Birth-Death Markov Processes, Queuing Systems, Theory of Games
