data.solver maximises, minimises or targets a value in an objective cell by
changing variable cells under <=, >=, =, int and bin constraints. Simplex LP
linearises the model through recalculation, checks linearity and solves it
with a two-phase simplex; integers use branch and bound. The GRG Nonlinear
choice runs an augmented-Lagrangian projected-gradient method. The model is
saved as hidden solver_* names; Solver Parameters and Solver Results dialogs.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Progress docs per craftrules standards/progress-docs.md: target-app parity, gaps, roadmap with alpha gate, readiness by audience (full / mainstream / essentials) with Opus 5.5 hours, and feature, format, hardware, UI and localization parity docs.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
