Abstract
Ten full-matrix problems and thirteen sparse-matrix problems, all based on chemical engineering problems, are used to perform a comprehensive test of iterative nonlinear equation solving techniques, in particular the techniques used for computing the correction step, and for updating sparse Jacobian matrices. Comparisons are made on the basis of both efficiency and reliability. Results indicate that Powell's dogleg correction step performs slightly better than the quasi-Newton step. Schubert's sparse Jacobian update performs very well, but the best overall is Bogle and Perkins's new least-relative-change update, at least when combined with the dogleg correction step.
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