This article studies the classical MDS and dwMDS location algorithm.On this basis, steepest descent algorithm is introduced to replace SMACOF algorithm as optimization objective function. The results show that the steepest descent method as the optimization objective function is simple and easy to implement. Compared with the dwMDS method based on SMACOF algorithm, the distributed MDS positioni...

It is shown that the steepest descent and Newton’s method for unconstrained nonconvex optimization under standard assumptions may be both require a number of iterations and function evaluations arbitrarily close to O(ǫ) to drive the norm of the gradient below ǫ. This shows that the upper bound of O(ǫ) evaluations known for the steepest descent is tight, and that Newton’s method may be as slow a...

| In classic backpropagation nets, as introduced by Rumelhart et al. 1], the weights are modiied according to the method of steepest descent. The goal of this weight modiication is to minimise the error in net-outputs for a given training set. Basing upon Jacobs' work 2], we point out drawbacks of steepest descent and suggest improvements on it. These yield a backpropagation net, which adjusts ...

In this paper we use steepest descent method for solving zero-one nonlinear programming problem. Using penalty function we transform this problem to an unconstrained optimization problem and then by steepest descent method we obtain the original problem optimal solution. 2007 Elsevier Inc. All rights reserved.