A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
We introduce a new algorithm for a class of smooth constrained minimization problems which is an iterative scheme that generates a sequence of feasible points that approximates the constraints set by a sequence of balls, and is accordingly called the Moving Balls Approximation Algorithm (MBA). The computational simplicity of MBA, which uses first order data information makes it suitable for large scale problems. Theoretical and computational properties of MBA and of some variant, in its primaldoi:10.1137/090763317 fatcat:l5cjkksbwrardhmpagkno2jmz4