Generalized Disjunctive Programming

Michael L. Bynum, Gabriel A. Hackebeil, William E. Hart, Carl D. Laird, Bethany L. Nicholson, John D. Siirola, Jean-Paul Watson and David L. Woodruff
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Michael L. Bynum: Sandia National Laboratories
Gabriel A. Hackebeil: Deepfield Nokia
William E. Hart: Sandia National Laboratories
Carl D. Laird: Sandia National Laboratories
Bethany L. Nicholson: Sandia National Laboratories
John D. Siirola: Sandia National Laboratories
Jean-Paul Watson: Lawrence Livermore National Laboratory
David L. Woodruff: University of California

Chapter Chapter 11 in Pyomo — Optimization Modeling in Python, 2021, pp 171-180 from Springer

Abstract: Abstract This chapter documents how to express and solve Generalized Disjunctive Programs (GDPs). GDP models provide a structured approach for describing logical relationships in optimization models.We show how Pyomo blocks provide a natural base for representing disjuncts and forming disjunctions, and we how to solve GDP models through the use of automated problem transformations.

Date: 2021
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DOI: 10.1007/978-3-030-68928-5_11

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