├── .gitignore ├── LICENSE ├── README.md ├── aa2020 ├── README.md ├── notebooks │ ├── Homework_1.ipynb │ ├── Homework_2.ipynb │ ├── Homework_3.ipynb │ ├── KnapsackProblem.ipynb │ ├── LPwithTwoVariables.ipynb │ ├── MagicSquare.ipynb │ ├── N-Queens.ipynb │ ├── Python_in_a_Nutshell.ipynb │ ├── Sudoku.ipynb │ └── TSP.ipynb └── python │ ├── README.md │ ├── basic_sir_fitting.py │ ├── fonts.py │ ├── magic_square.py │ ├── naive_reverse_dijkstra.py │ ├── ot_1D.py │ ├── ot_2D.py │ ├── plot_shortest_path_tree.py │ ├── simplex.py │ ├── sudoku.py │ └── tsp_exercise.py ├── aa2021 ├── README.md ├── notebooks │ ├── CVRP.ipynb │ ├── KnapsackProblem.ipynb │ ├── Lego Problems.ipynb │ ├── LinearClassification.ipynb │ ├── MagicSquare.ipynb │ ├── N-Queens.ipynb │ ├── Python_e_Pyomo.ipynb │ ├── Python_e_Pyomo_soluzione.ipynb │ ├── Python_in_a_Nutshell.ipynb │ ├── SteelBlending.ipynb │ ├── banknote_train.csv │ └── staff.lp └── python │ ├── README.md │ ├── borgo.jpg │ ├── classificationBanknote.py │ ├── classificationGaussian2D.py │ ├── color_transfer.py │ ├── color_transfer_aula.py │ ├── cvrp.py │ ├── cvrp_half_sol.py │ ├── misc.lp │ ├── miscelazione.py │ ├── miscelazione_ip.py │ ├── notte.jpg │ ├── tsp_exercise.py │ └── tsp_solution.py ├── aa2022 ├── README.md ├── notebooks │ ├── CVRP.ipynb │ ├── ColorTransfer.ipynb │ ├── LinearClassification.ipynb │ ├── Python_and_Pyomo.ipynb │ ├── Python_in_a_Nutshell.ipynb │ ├── Steel_Planning.ipynb │ └── TSP.ipynb └── scripts │ ├── blending_IP.py │ ├── blending_LP.py │ ├── classificationBanknote.py │ ├── classificationBreastCancer.py │ ├── classificationGaussian2D.py │ ├── color_transfer.py │ ├── cvrp.py │ ├── magic_square.py │ ├── steel_production.py │ ├── sudoku.py │ ├── tsp.py │ ├── tsp_aula.py │ └── tsp_heuristics.py ├── aa2023 ├── README.md ├── notebooks │ ├── ColorTransfer.ipynb │ ├── Lego_Problems.ipynb │ ├── LinearClassification.ipynb │ ├── Python_and_Pyomo.ipynb │ ├── Python_in_a_Nutshell.ipynb │ ├── Python_in_a_Nutshell_solutions.ipynb │ ├── SemanticSegmentation.ipynb │ ├── Steel_Planning.ipynb │ ├── TSP.ipynb │ ├── TrainingBNN.ipynb │ ├── borgo.jpg │ ├── notte.jpg │ └── picture32_1009.png └── scripts │ ├── NN_and.py │ ├── NN_xor.py │ ├── RNAfolding.py │ ├── blending_IP.py │ ├── blending_LP.py │ ├── bnn_mnist.py │ ├── color_transfer.py │ ├── graph_coloring.py │ ├── identity_nn.py │ ├── lego1.lp │ ├── lego2.lp │ ├── logical_nn_and_or_xor.py │ ├── magic_square.py │ ├── notte.jpg │ ├── segmentation.py │ ├── test_rel.py │ ├── tsp.py │ └── urlo.jpg ├── aa2024 ├── README.md ├── notebooks │ ├── Lego_Problems.ipynb │ ├── Linear_Regression.ipynb │ ├── Python_and_Gurobi.ipynb │ ├── Python_in_a_Nutshell.ipynb │ ├── Python_in_a_Nutshell_solutions.ipynb │ ├── Steel_Planning.ipynb │ ├── Student_Challenge_1.ipynb │ ├── TSP.ipynb │ ├── TrainingBNN.ipynb │ └── production.lp └── scripts │ ├── B-SVM.py │ ├── CNN.py │ ├── NN_and.py │ ├── NN_xor.py │ ├── Xor_aula.py │ ├── colorTransfer.py │ ├── convolve.py │ ├── grb_atsp.py │ ├── grb_atsp_sec.py │ ├── grb_tsp.py │ ├── knapsack.py │ ├── regression_diabete.py │ ├── regression_sin.py │ ├── square_magic.py │ ├── steel.py │ ├── test-all.log │ └── xor_uncertain.py ├── data ├── E-n101-k8.vrp ├── E-n22-k4.vrp ├── E-n23-k3.vrp ├── E-n30-k3.vrp ├── E-n33-k4.vrp ├── E-n51-k5.vrp ├── X-n101-k25.vrp ├── all_nine_four.csv ├── all_three_four.csv ├── banknote_train.csv ├── borgo.PNG ├── borgo.jpg ├── breast_cancer_train.csv ├── insurance_train.csv ├── notte.jpg ├── picture32_1007.png ├── picture32_1009.png ├── train_nine_four.csv └── train_three_four.csv ├── notebooks ├── ColorTransfer.ipynb ├── Linear_Regression.ipynb ├── Python_and_Gurobi.ipynb ├── Python_in_a_Nutshell.ipynb ├── Steel_Planning.ipynb ├── TSP.ipynb ├── TrainingBNN.ipynb ├── borgo.jpg ├── insurance_train.csv ├── notte.jpg └── picture32_1009.png └── scripts ├── atsp.py ├── colorTransfer.py ├── regression_diabete.py ├── regression_sin.py ├── square_magic.py └── steel.py /.gitignore: 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