RAL-TR-97-054 A numerical comparison between theLANCELOT and MINOS packagesfor large-scale constrained optimizationI

We present the results of a numerical comparison of two nonlinear optimization packages capable of handling large problems, MINOS 5.5 and LANCELOT (Release A). The comparison was performed using over 900 constrained and unconstrained problems from the CUTE collection. With the default options, LANCELOT makes use of rst and second derivatives, while MINOS requires gradients but cannot use higher derivatives. We conclude that LANCELOT is usually more eecient in terms of the number of function and derivative evaluations. If the latter are inexpensive, MINOS may require less CPU time unless there are many degrees of freedom. LANCELOT proves to be less reliable than MINOS on linear programming problems, but somewhat more reliable on problems involving nonlinear constraints.

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