1. A method for optimizing a system, comprising: receiving one or more historical values for each of a plurality of system parameters; grouping the system parameters into controllable parameters, non-controllable parameters, and performance parameters; determining a first set of predictors from the non-controllable parameters using the historical values of these non-controllable parameters; for each predictor in the first set of predictors, determining one or more optimal time instances at which a value of each predictor in the first set of predictors is measured using non-uniform time scales; storing the optimal time instances for each predictor in the first set of predictors as a second set of predictors; establishing one or more constraints for each of the controllable parameters; constructing a dynamic model based on the second set of predictors, the controllable parameters, and the performance parameters; and optimizing the dynamic model with a non-gradient-based algorithm.