A global optimization method, αBB, for process design

C. S. Adjiman, I. P. Androulakis, C. D. Maranas, C. A. Floudas

Research output: Contribution to journalArticlepeer-review

99 Scopus citations


A global optimization algorithm, αBB, for twice-differentiable NLPs is presented. It operates within a branch-and-bound framework and requires the construction of a convex lower bound-ing problem. A technique to generate such a valid convex underestimator for arbitrary twice-differentiable functions is described. The αBB has been applied to a variety of problems and a summary of the results obtained is provided.

Original languageEnglish (US)
Pages (from-to)S419-S424
JournalComputers and Chemical Engineering
Issue numberSUPPL.1
StatePublished - Jan 1 1996

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Computer Science Applications


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