Monotone variable-metric algorithm for linearly constrained nonlinear programming

A new method for linearly constrained nonlinear programming is proposed. Th is method follows affine scaling paths defined by systems of ordinary diffe rential equations and it is fully parallelizable. The convergence of the me thod is proved for a nondegenerate problem with pseudoconvex objective func tion. In practice, the algorithm works also under more general assumptions on the objective function. Numerical results obtained with this computation al method on several test problems are shown.