The goal of this thesis is to develop a Web platform that makes it as easy as possible to model and solve optimization problems. The modeling portion of the project is based on the Markup Language for Mixed Integer Linear Programs [Bund-Becker '19], which will also be discussed and modified in this thesis. Furthermore, the focus of my work will be on the implementation of the front end. This includes the user interface, the modeling of mixed-integer problems, and a synthesizer, which translates a modeled problem for a solver. Finally, to solve problems, a connection to a solver must be established.
The developed Web platform offers different views for modeling mixed-integer problems, depending on the background of the user. The implemented synthesizer translates modeled problems into a variant of the LP format, which can then be sent to the connected back end and be solved by the provided solvers. In summary, the platform makes it possible to model optimization problems intuitively and solve them directly. Lastly, the modular implementation of the platform allows further possible extensions, such as a market for templates, where modeled problems and sub-problems can be shared.
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