PySCIPOpt: Mathematical Programming in Python with the SCIP Optimization Suite

  • Stephen Maher
  • Matthias Miltenberger
  • João Pedro Pedroso
  • Daniel Rehfeldt
  • Robert Schwarz
  • Felipe Serrano
Conference paper

DOI: 10.1007/978-3-319-42432-3_37

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9725)
Cite this paper as:
Maher S., Miltenberger M., Pedroso J.P., Rehfeldt D., Schwarz R., Serrano F. (2016) PySCIPOpt: Mathematical Programming in Python with the SCIP Optimization Suite. In: Greuel GM., Koch T., Paule P., Sommese A. (eds) Mathematical Software – ICMS 2016. ICMS 2016. Lecture Notes in Computer Science, vol 9725. Springer, Cham

Abstract

SCIP is a solver for a wide variety of mathematical optimization problems. It is written in C and extendable due to its plug-in based design. However, dealing with all C specifics when extending SCIP can be detrimental to development and testing of new ideas. This paper attempts to provide a remedy by introducing PySCIPOpt, a Python interface to SCIP that enables users to write new SCIP code entirely in Python. We demonstrate how to intuitively model mixed-integer linear and quadratic optimization problems and moreover provide examples on how new Python plug-ins can be added to SCIP.

Keywords

SCIP Mathematical optimization Python Modeling 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Stephen Maher
    • 1
  • Matthias Miltenberger
    • 1
  • João Pedro Pedroso
    • 2
  • Daniel Rehfeldt
    • 1
  • Robert Schwarz
    • 1
  • Felipe Serrano
    • 1
  1. 1.Zuse Institute BerlinBerlinGermany
  2. 2.Faculdade de Ciências da Universidade do PortoPortoPortugal

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