ODE versus SQP methods for constrained optimization
We review some methods which are designed to solve equality constrained minimization problems by following the trajectory defined by a system of ordinary differential equations. The numerical performance of a number of these methods is compared with that of some popular sequential quadratic programming (SQP) algorithms. On a set of eighteen ``difficult'' test problems, we observe that several of the ODE methods are more successful than any of the SQP techniques. We suggest that these experimental results indicate the need for research both to analyze and develop new ODE techniques and also to strengthen the currently available SQP algorithms.
scientific article; zbMATH DE number 4070212