Optimization, Python, Linear Optimization, Operations Research.
max(d.values()))) Let’s declare objective function. SciPy def objective(x): obj_func = sum(x[idx]*cost2d[idx//len(J), idx%len(J)] for idx in range(cost2d.size)) return obj_func PuLP objective = pulp.LpAffineExpression(e = [(x[i,j],cost[i,j]) for i,j in x], name = 'Objective function') model =