simulation in optimization problems has become computationally expensive. This paper provides a smart data driven mechanism to … optimization problems by using training instances derived from the evaluations of the true objective functions. The surrogate … in computational time of optimization, while preserving the accuracy. These surrogate models also show robustness in …

electricity consumption at both individual household and national level? First, we developed an hourly optimization model for …, radiation, (dynamic) electricity price, and feed-in tariff. By comparing the optimization to the reference scenario, we show the …

-criteria optimization framework. To initialize such a framework, a non-linear autoregressive network with exogenous inputs (NARX) has been …

implementation. In this article, we present the crop rotation optimization model CropRota. CropRota integrates agronomic criteria and …