Data Science, Machine Learning, Causal Inference, AI, Linear Programming.
solver.Solve() assignments = [] values = [] if status == pywraplp.Solver.OPTIMAL or status == pywraplp.Solver.FEASIBLE: for i in range(num_custs): for j in range(num_treatments): # Test if x[i,j] is 1 (with tolerance for floating point arithmetic). if x[i, j].solution_value() > -0.5: