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Generation techniques for linear programming instances with controllable properties

  • Simon BowlyEmail author
  • Kate Smith-Miles
  • Davaatseren Baatar
  • Hans Mittelmann
Full Length Paper
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Abstract

This paper addresses the problem of generating synthetic test cases for experimentation in linear programming. We propose a method which maps instance generation and instance space search to an alternative encoded space. This allows us to develop a generator for feasible bounded linear programming instances with controllable properties. We show that this method is capable of generating any feasible bounded linear program, and that parameterised generators and search algorithms using this approach generate only feasible bounded instances. Our results demonstrate that controlled generation and instance space search using this method achieves feature diversity more effectively than using a direct representation.

Keywords

Linear programming Instance generation Controllable properties Encoded space 

Mathematics Subject Classification

90C05 68W40 90-08 

Notes

Acknowledgements

The authors would like to thank the anonymous referees from Mathematical Programming Computation whose thorough comments significantly improved the focus and quality of this work.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society 2019

Authors and Affiliations

  • Simon Bowly
    • 1
    Email author
  • Kate Smith-Miles
    • 1
  • Davaatseren Baatar
    • 2
  • Hans Mittelmann
    • 3
  1. 1.School of Mathematics and StatisticsUniversity of MelbourneParkvilleAustralia
  2. 2.School of Mathematical SciencesMonash UniversityClaytonAustralia
  3. 3.School of Mathematical and Statistical SciencesArizona State UniversityTempeUSA

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