Research Article
Pareto Optimal Solutions for Stochastic Dynamic Programming Problems via Monte Carlo Simulation
algorithm | read input; | for until sampleSize do | generate randomly a sequence of disturbances with a | given probability distribution function; | find a sequence of decision variables that optimizes | the objective-function, as if it were a | deterministic dynamic programming problem; |
end for | mount the Pareto front of the decision variables, | weighted by its quantiles; | take the box-plot, the average, or any other quantile of | these variables as the answer of the problem. | end algorithm |
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