Pyomo.GDP: an ecosystem for logic based modeling and optimization development

Chen, Qi; Johnson, Emma S.; Bernal, David E.; Valentin, Romeo; Kale, Sunjeev; Bates, Johnny; Siirola, John D.; Grossmann, Ignacio E.

doi:10.1007/s11081-021-09601-7

Title: Pyomo.GDP: an ecosystem for logic based modeling and optimization development

Journal Article · Fri Apr 23 00:00:00 EDT 2021 · Optimization and Engineering

DOI:https://doi.org/10.1007/s11081-021-09601-7· OSTI ID:1781543

Chen, Qi ^[1]; Johnson, Emma S. ^[2]; Bernal, David E. ^[1]; Valentin, Romeo ^[1]; Kale, Sunjeev ^[1]; Bates, Johnny ^[1]; Siirola, John D. ^[2]; Grossmann, Ignacio E. ^[1]

Carnegie Mellon Univ., Pittsburgh, PA (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

We present three core principles for engineering-oriented integrated modeling and optimization tool sets—intuitive modeling contexts, systematic computer-aided reformulations, and flexible solution strategies—and describe how new developments in Pyomo.GDP for Generalized Disjunctive Programming (GDP) advance this vision. We describe a new logical expression system implementation for Pyomo.GDP allowing for a more intuitive description of logical propositions. The logical expression system supports automated reformulation of these logical constraints to linear constraints. We also describe two new logic-based global optimization solver implementations built on Pyomo.GDP that exploit logical structure to avoid “zero-flow” numerical difficulties that arise in nonlinear network design problems when nodes or streams disappear. These new solvers also demonstrate the capability to link to external libraries for expanded functionality within an integrated implementation. We present these new solvers in the context of a flexible array of solution paths available to GDP models. Finally, we present results on a new library of GDP models demonstrating the value of multiple solution approaches.

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Research Organization:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Office of Fossil Energy (FE); USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC04-94AL85000; NA0003525

OSTI ID:: 1781543

Report Number(s):: SAND-2021-1731J; 694272

Journal Information:: Optimization and Engineering, Vol. 23, Issue 1; ISSN 1389-4420

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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