Nonlinear Programming with Pyomo

William E. Hart (), Carl Laird (), Jean-Paul Watson () and David L. Woodruff ()
Additional contact information
William E. Hart: Sandia National Laboratories
Carl Laird: Texas A&M
Jean-Paul Watson: Sandia National Laboratories
David L. Woodruff: University of California, Davis

Chapter Chapter 8 in Pyomo – Optimization Modeling in Python, 2012, pp 105-129 from Springer

Abstract: Abstract The modeling components that are described earlier in the book can be used within nonlinear models. This chapter describes the nonlinear programming capabilities of Pyomo. It presents all the nonlinear expressions and functions that are supported, and it provides some tips for formulating and solving nonlinear programming problems. Pyomo makes use of the interface provided by the AMPL Solver Library to provide efficient expression evaluation and automatic differentiation. Use of the AMPL Solver Library means that any AMPL-enabled solver should be usable as a solver within the Pyomo framework. This chapter also provides several real-world examples to illustrate formulating and solving nonlinear programming problems.

Keywords: Nonlinear Programming; Continuously Stir Tank Reactor; Nonlinear Programming Problem; Deer Population; Outlet Concentration (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/978-1-4614-3226-5_8

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