Mathematical Programming Computation, Volume 10, Issue 2, June 2018

Font Size:  Small  Medium  Large

pyomo.dae: a modeling and automatic discretization framework for optimization with differential and algebraic equations

Bethany Nicholson, John D. Siirola, Jean-Paul Watson, Victor M. Zavala, Lorenz T. Biegler

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 stan- dard, 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 trans- form 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 con- cepts, discretization schemes, and the benchmarking of state-of-the-art optimization solvers.


Full Text: PDF

mpc footer
© MPS 2008-2018