Mathematical Programs with Equilibrium Constraints
William E. Hart,
Carl D. Laird,
Jean-Paul Watson,
David L. Woodruff,
Gabriel A. Hackebeil,
Bethany L. Nicholson and
John D. Siirola
Additional contact information
William E. Hart: Sandia National Laboratories
Carl D. Laird: Sandia National Laboratories
Jean-Paul Watson: Sandia National Laboratories
David L. Woodruff: University of California, Davis
Gabriel A. Hackebeil: University of Michigan
Bethany L. Nicholson: Sandia National Laboratories
John D. Siirola: Sandia National Laboratories
Chapter Chapter 12 in Pyomo — Optimization Modeling in Python, 2017, pp 211-222 from Springer
Abstract:
Abstract This chapter documents how to formulate mathematical programs with equilibrium constraints (MPECs), which naturally arise in a wide range of engineering and economic systems. We describe Pyomo components for complementarity conditions, and transformation capabilities that automate the reformulation of MPEC models, and meta-solvers that leverage these transformations to support global and local optimization of MPEC models.
Keywords: Mathematical Program; Sequential Quadratic Programming; Nonlinear Transformation; Equilibrium Constraint; Complementarity Condition (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-319-58821-6_12
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DOI: 10.1007/978-3-319-58821-6_12
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