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International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research

CPAIOR 2021: Integration of Constraint Programming, Artificial Intelligence, and Operations Research pp 1–25Cite as

Supercharging Plant Configurations Using Z3

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12735))

Abstract

We describe our experiences using Z3 for synthesizing and optimizing next generation plant configurations for a car manufacturing company (The views expressed in this writing are our own. They make no representation on behalf of others). Our approach leverages unique capabilities of Z3: a combination of specialized solvers for finite domain bit-vectors and uninterpreted functions, and a programmable extension that we call constraints as code. To optimize plant configurations using Z3, we identify useful formalisms from Satisfiability Modulo Theories solvers and integrate solving capabilities for the resulting non-trivial optimization problems.

M. Levatich—Work performed while an intern at Microsoft.

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Author information

Authors and Affiliations

  1. Microsoft, Redmond, WA, USA

    Nikolaj Bjørner

  2. Columbia University, New York City, NY, USA

    Maxwell Levatich

  3. Microsoft, Cambridge, UK

    Nuno P. Lopes & Andrey Rybalchenko

  4. Microsoft, Sunnyvale, CA, USA

    Chandrasekar Vuppalapati

Authors
  1. Nikolaj Bjørner
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  2. Maxwell Levatich
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  3. Nuno P. Lopes
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  4. Andrey Rybalchenko
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  5. Chandrasekar Vuppalapati
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Corresponding author

Correspondence to Nikolaj Bjørner .

Editor information

Editors and Affiliations

  1. Monash University, Melbourne, VIC, Australia

    Peter J. Stuckey

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Bjørner, N., Levatich, M., Lopes, N.P., Rybalchenko, A., Vuppalapati, C. (2021). Supercharging Plant Configurations Using Z3. In: Stuckey, P.J. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2021. Lecture Notes in Computer Science(), vol 12735. Springer, Cham. https://doi.org/10.1007/978-3-030-78230-6_1

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  • DOI: https://doi.org/10.1007/978-3-030-78230-6_1

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