Cs. Adjiman et al., A GLOBAL OPTIMIZATION METHOD, ALPHA-BB, FOR GENERAL TWICE-DIFFERENTIABLE CONSTRAINED NLPS - II - IMPLEMENTATION AND COMPUTATIONAL RESULTS, Computers & chemical engineering, 22(9), 1998, pp. 1159-1179
Part I of this paper (Adjiman et al., 1998a) described the theoretical
foundations of a global optimization algorithm, the alpha BB algorith
m, which can be used to solve problems belonging to the broad class of
twice-differentiable NPLs. For any such problem, the ability to autom
atically generate progressively tighter convex lower bounding problems
at each iteration guarantees the convergence of the branch-and-bound
alpha BB algorithm to within epsilon of the global optimum solution. S
everal methods were presented for the construction of valid convex und
erestimators for general nonconvex functions. In this second part, the
performance of the proposed algorithm and its alternative underestima
tors is studied through their application to a variety of problems. An
implementation of the alpha BB is described and a number of rules for
branching variable selection and variable bound updates are shown to
enhance convergence rates. A user-friendly parser facilitates problem
input and provides flexibility in the selection of an underestimating
strategy. In addition, the package features both automatic differentia
tion and interval arithmetic capabilities. Making use of all the avail
able options, the alpha BB algorithm successfully identifies the globa
l optimum solution of small literature problems, of small and medium s
ize chemical engineering problems in the areas of reactors network des
ign, heat exchanger network design, reactor-separator network design,
of generalized geometric programming problems for design and control,
and of batch process design problems with uncertainty. (C) 1998 Elsevi
er Science Ltd. All rights reserved.