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Package ConstraintTrees.jl
provides a simple data structure ConstraintTree
for organizing the contents of various constrained optimization problems. As a
main goal, it abstracts over the distinction between constraints and variables,
allowing much tidier, nicer and extensible representation of many kinds of
complex constraint systems. The primary purpose is to support constraint-based
metabolic modeling within
COBREXA.jl.
ConstraintTrees are intended to be used with JuMP, but the package does not depend on JuMP -- instead it is completely generic and lightweight, and may be used with any other constraint-solving framework. The documentation describes a typical use of ConstraintTrees for describing and solving constrained linear (LP), quadratic (QP) and mixed-integer (MILP) problems using JuMP, together with copy-pasteable code snippets that provide the integration.
ConstraintTrees package is actively maintained and open for extensions. Feel free to discuss changes and ideas via issues and pull requests.
ConstraintTrees.jl
was developed at the Luxembourg Centre for Systems
Biomedicine of the University of Luxembourg
(uni.lu/lcsb)
and at Institute for Quantitative and Theoretical Biology at Heinrich Heine
University Düsseldorf (qtb.hhu.de).
The development was supported by European Union's Horizon 2020 Programme under
PerMedCoE project (permedcoe.eu),
agreement no. 951773.