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 …

is measured by GDP per capita. The optimization shows that the level of GERD equal to 2.6 maximizes the GDP per capita …

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 …

integration of soil status dependent sequestration rates in land use decision optimization models. The soil status is represented …

excellence has become a key issue. This book introduces a novel approach focusing on the autonomous optimization of business … Optimization. …

efficiently control these systems and to satisfy the different interests as good as possible, mathematical optimization models can … be used to support operational decisions. Common approaches for reservoir optimization apply linear optimization … volume in a reservoir or to account for the hydropower equation. When the non-linear equations form a non-convex optimization …