DynamicOED.jl
DynamicOED.jl: A Julia package for solving optimum experimental design problems - Published in JOSS (2024)
JuMP
Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
https://github.com/SciML/Optimization.jl
Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
pyscipopt-ml
Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs
https://github.com/cog-imperial/omlt
Represent trained machine learning models as Pyomo optimization formulations
Boscia
Mixed-Integer Convex Programming: Branch-and-bound with Frank-Wolfe-based convex relaxations
https://github.com/cn-upb/b-jointsp
Joint placement and scaling of bidirectional network services with stateful virtual or physical network functions
binpacking2d
Exact solutions for two-dimensional bin packing problems by branch-and-cut
pyrddlgym-gurobi
Gurobi compilation of RDDL description files to mixed-integer programs, and optimization tools.