Supplementary Materials: A comprehensive approach for an approximative integration of nonlinear-bivariate functions in mixed-integer linear programming (MILP) models
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2022-04-08
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The architecture consists of 3 modules: Master Module, Approximation Module and MILP Module. In the master module, the nonlinear bivariate functions are defined and the input data for the optimization module is managed. It should be mentioned that univariate functions can also be defined in addition to the bivariate functions, but this should not be considered further, since the data flows are analogously. The functions are passed from the master module to the approximation module, where the functions are transformed from a continuous surface to a piecewise-constant-linear mesh. In a next step, the meshes are passed back to the master module and stored in the input data. The complete input data – one-dimensional and multi-dimensional parameters – are transferred to the optimization program. In the MILP, the constraints for the meshes are stored, which are independent of the specific, initially defined function.
Note: For running the code, an application scenario needs to be integrated.
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Except where otherwise noted, this license is described as Open Data Commons Attribution License (ODC-By) v1.0