MAiNGO – McCormick-based Algorithm for mixed-integer Nonlinear Global Optimization

点击翻译按钮获取中文摘要

The objective of this project is to develop and provide a reliable and novel open-source software for deterministic global optimization of mixed-integer nonlinear optimization problems. A first version of MAiNGO is already being developed at the chair for Process Systems Engineering (AVT.SVT) RWTH Aachen University with the goal of an open-source publication. In contrast to other state-of-the-art deterministic global optimization solvers, MAiNGO does not increase the dimensionality of the user-defined optimization problem. This is achieved through the reduced-space formulation and the application of the so-called McCormick relaxations. The McCormick relaxations are constructed via the open-source package MC++. MAiNGO implements a specialized heuristic for the improvement of the resulting McCormick relaxations and also specialized relaxations for specific intrinsic functions (including functions commonly found in the field of chemical engineering). We have already shown, that MAiNGO exhibits computational advantages for problems formulated in a reduced-space manner. Problems profiting from a reduced-space formulation can be found in flowsheet optimization or data-driven optimization with artificial neural networks.MAiNGO can be used, adapted and extended by the research community. Currently, MAiNGO is a prototype software and misses an adequate documentation and unit testing. Moreover, the software has to be tested on published benchmarks from the global optimization community. The implementation of interfaces to common programming and modelling languages also represents one of goals of this project.