The recent advances in mathematical programming approaches applied to
process design and operation problems have produced a need for the abi
lity to find the global optimum of a nonconvex problem containing disc
rete: variables (a nonconvex MINLP). This paper presents a modified ve
rsion of the reformulation/spatial branch-and-bound algorithm of Smith
and Pantelides (1996) for the solution of such problems. The algorith
m is implemented within the gPROMS modelling environment (Barton and P
antelides, 1994) and tested on several MINLP problems arising from pro
cess engineering applications.