AMPL Model Colaboratory
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Updated
May 8, 2024 - Jupyter Notebook
AMPL Model Colaboratory
Nix flake and expressions for tools from the SCIP Optimization Suite.
MiniZinc ↔ .NET
LPFramework is an abstraction to programmatically formulate mixed-integer linear optimization (MILP) problems, which can then be solved using open-source/commercial solvers.
Linear optimization software
Dorado observation planning and scheduling simulations
Multiobjective black-box optimization using gradient-boosted trees
Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
Importance Sampling and Linear Programming based Enumerating and Weighing of Trapping sets in LDPC codes, ISING models and related DNN Arch( Transformer, RBM, BM, SPN und etc),
Feasibility study on using mixed-integer-linear programming for solving optimal pump scheduling problem in water distribution networks.
Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs
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.
Minotaur Toolkit for Mixed-Integer Nonlinear Optimization
Mixed integer linear program and genetic algorithm for post-prognostics production scheduling.
FelooPy: Efficient & Feature-Rich Integrated Decision Environment
Efficient modeling interface for mathematical optimization in Python
Represent trained machine learning models as Pyomo optimization formulations
Mixed-Integer Convex Programming: Branch-and-bound with Frank-Wolfe-based convex relaxations
Optimal experimental design of ODE and DAE systems in julia
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