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pyomo.dae: A Modeling and Automatic Discretization Framework for Optimization with Differential and Algebraic Equations

Bethany Nicholson(bethanylnicholson***at***gmail.com)
John D. Siirola(jdsiiro***at***sandia.gov )
Jean-Paul Watson(jwatson***at***sandia.gov )
Victor M. Zavala(zavalatejeda***at***wisc.edu )
Lorenz T. Biegler(biegler***at***cmu.edu )

Abstract: We describe pyomo.dae, an open source Python-based modeling framework that enables high-level abstract specification of optimization problems with differential and algebraic equations. The pyomo.dae framework is integrated with the Pyomo open source algebraic modeling language, and is available at http: //www.pyomo.org. One key feature of pyomo.dae is that it does not restrict users to standard, predefined forms of differential equations, providing a high degree of modeling flexibility and the ability to express constraints that cannot be easily specified in other modeling frameworks. Other key features of pyomo.dae are the ability to specify optimization problems with high-order differential equations and partial differential equations, defined on restricted domain types, and the ability to automatically transform high-level abstract models into finite-dimensional algebraic problems that can be solved with off-the-shelf solvers. Moreover, pyomo.dae users can leverage existing capabilities of Pyomo to embed differential equation models within stochastic and integer programming models and mathematical programs with equilibrium constraint formulations. Collectively, these features enable the exploration of new modeling concepts, discretization schemes, and the benchmarking of state-of-the-art optimization solvers.

Keywords: Dynamic optimization, Mathematical modeling, Algebraic modeling language, DAE constrained optimization, PDE constrained optimization

Category 1: Optimization Software and Modeling Systems (Modeling Languages and Systems )

Category 2: Applications -- Science and Engineering (Optimization of Systems modeled by PDEs )

Category 3: Nonlinear Optimization (Systems governed by Differential Equations Optimization )

Citation:

Download: [PDF]

Entry Submitted: 05/25/2016
Entry Accepted: 05/25/2016
Entry Last Modified: 05/25/2016

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