A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
New methods for calculating $$\alpha $$ BB-type underestimators
2013
Journal of Global Optimization
Most branch-and-bound algorithms in global optimization depend on convex underestimators to calculate lower bounds of a minimization objective function. The αBB methodology produces such underestimators for sufficiently smooth functions by analyzing interval Hessian approximations. Several methods to rigorously determine the αBB parameters have been proposed, varying in tightness and computational complexity. We present new polynomial-time methods and compare their properties to existing
doi:10.1007/s10898-013-0057-y
fatcat:fenxrv2tmfgnxcd3hahlh4tzqm