The Bounded Linearized Iteration for Natural Gas (BLING) algorithm implements a special-purpose sparse matrix formulation of the steady-state optimization problem for pipeline networks including non-ideal California Natural Gas Association (CNGA) equation of state (EOS). The formulation maximizes economic surplus and minimizes the energy used for gas compression subject to pressure, flow, and engineering constraints. The nonlinear program is solved with a sequential linear programming (SLP) algorithm that ensures feasibility, converges rapidly, and scales beyond the capabilities of commercial general-purpose solvers. Numerical studies show reliable solves for networks of unprecedented scale, including synthetic cases on the scale of, e.g., all pipelines in Texas or the entire continental U.S., as well as standard GASLIB instances. The method accounts for a non-ideal gas EOS while rapidly and consistently solving planning or operational problems in gas transmission. The code also includes a Newton fixed-point solver that is used to verify the constraint feasibility of the optimization problem solution to a precise tolerance.