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OMLT
Represent trained machine learning models as Pyomo optimization formulationsromodel
Modeling robust optimization problems in Pyomoentmoot
Multiobjective black-box optimization using gradient-boosted treesGPdoemd
Design of experiments for model discrimination using Gaussian process surrogate modelssuspect
Special Structure Detection for PyomoSnAKe
Repository for paper: "SnAKe: Bayesian Optimization with Pathwise Exploration".pooling-network
tree_kernel_gp
min_matches_heuristics
Source code of the methods proposed in "Dimitrios Letsios, Georgia Kouyialis, Ruth Misener. Heuristics with Performance Guarantees for the Minimum Number of Matches Problem in Heat Recovery Network Design. Computers and Chemical Engineering 113:57-85, 2018".".pypopt
Bindings to Ipopt C++ library for Python. šrogp
Modeling Gaussian Processes in PyomoPartitionedFormulations_NN
Implementation of partition-based formulations for mixed-integer optimization of trained ReLU neural networkstwo_stage_scheduling
Exact lexicographic scheduling methods and approximate recovery strategies for two-stage makespan schedulingGNN_MIP_CAMD
Repository for paper: "Optimizing over trained GNNs via symmetry breaking".OMLT_CAMD
Repository for paper: "Augmenting optimization-based molecular design with graph neural networks".galini-dashboard
Dashboard for the GALINI SolverDCBO
Repository for paper: "Dependence in constrained Bayesian optimization: When do we need it and how does it help?".Partial-Lasserre-relaxation-sparse-maxcut
drill-scheduling
Pyomo implementation of a drill scheduling case studymoo_trees
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