Retrospective on optimization

  • Biegler L
  • Grossmann I
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In this paper, we provide a general classification of mathematical optimization problems, followed by a matrix of applications that shows the areas in which these problems have been typically applied in process systems engineering. We then provide a review of solution methods of the major types of optimization problems for continuous and discrete variable optimization, particularly nonlinear and mixed-integer nonlinear programming (MINLP). We also review their extensions to dynamic optimization and optimization under uncertainty. While these areas are still subject to significant research efforts, the emphasis in this paper is on major developments that have taken place over the last 25 years. © 2003 Elsevier Ltd. All rights reserved.

Author-supplied keywords

  • Dynamic optimization
  • Linear programming
  • Mixed integer nonlinear programming
  • Nonlinear programming
  • Process optimization
  • Stochastic optimization

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