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Report grid cost from the solver's own quadrature - #32
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The NLP integrates the grid field with the Legendre quadrature at the collocation points, while the reported value summed the per-node grid_cost column, a left-endpoint rectangle rule over the intervals. The two disagree by up to 20% per solve and by a differing amount between solves of the same problem, so weighted-sum points could sit above the lower convex hull of their own Pareto front, which no weight can produce. Accumulate the grid term beside the objective during transcription, unscaled by auto_rescale_objective, and expose it as Base.grid_cost_value for TrajectoryResult.grid_cost to prefer. Fuel already avoided this by deriving fuel_cost from mass differences rather than recomputing the integral. TrajectoryResult.grid_cost therefore returns a different, correct number; its name, type and units are unchanged and the grid_cost column is untouched. Also assign the winning candidate's objective_value and grid_cost_value in multi-start, which previously reported the last start solved rather than the trajectory it returned.
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The NLP integrates the grid field with the Legendre quadrature at the collocation points, while the reported value summed the per-node grid_cost column, a left-endpoint rectangle rule over the intervals. The two disagree by up
to 20% per solve and by a differing amount between solves of the same problem, so weighted-sum points could sit above the lower convex hull of their own Pareto front, which no weight can produce. Accumulate the grid term
beside the objective during transcription, unscaled by auto_rescale_objective, and expose it as Base.grid_cost_value for TrajectoryResult.grid_cost to prefer. Fuel already avoided this by deriving fuel_cost from mass
differences rather than recomputing the integral.
TrajectoryResult.grid_cost therefore returns a different, correct number; its name, type and units are unchanged and the grid_cost column is untouched. Also assign the winning candidate's objective_value and grid_cost_value in
multi-start, which previously reported the last start solved rather than the trajectory it returned.