A specialized language for modeling discrete-time optimization problems with a clear graph-based structure, designed for researchers and engineers.
The Graph-Based Optimization Modeling Language (GBOML) is a modeling language for mathematical programming designed and implemented at the University of Liège, Belgium. GBOML enables the easy implementation of a broad class of structured mixed-integer linear programs typically found in applications ranging from energy system planning to supply chain management.
More precisely, the language is particularly well-suited for representing problems involving the optimization of discrete-time dynamical systems over a finite time horizon and possessing a block structure that can be encoded by a hierarchical hypergraph.
The language combines elements of both algebraic and object-oriented modeling languages in order to :
The GBOML parser, which is implemented in Python, turns GBOML input files into hierarchical graph data structures representing optimization models. The associated tool provides both a command-line interface and a Python API to construct models, and directly interfaces with a variety of open source and commercial solvers, including structure-exploiting ones.
RESEARCH HIGHLIGHTS
@article{Miftari2023, author = {Bardhyl Miftari, Mathias Berger, Guillaume Derval, Quentin Louveaux and Damien Ernst}, title = {GBOML: a structure-exploiting optimization modelling language in Python}, journal = {Optimization Methods and Software}, volume = {0}, number = {0}, pages = {1-30}, year = {2023}, publisher = {Taylor & Francis}, doi = {10.1080/10556788.2023.2246169}, URL = {https://doi.org/10.1080/10556788.2023.2246169}, eprint = {https://doi.org/10.1080/10556788.2023.2246169} }
