Benchmarks for Optimization Software

Benchmarks for Optimization Software: Here we provide information on testruns comparing different solution methods on standardized sets of testproblems, running on the same or on different computer systems. Benchmarking is a difficult area for nonlinear problems, since different codes use different criteria for termination. Although much effort has been invested in making results comparable, in a critical situation you should try the candidates of your choice on your specific application. Many benchmark results can be found in the literature, ..

References in zbMATH (referenced in 109 articles )

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  1. Cheung, Kevin K.H.; Gleixner, Ambros; Steffy, Daniel E.: Verifying integer programming results (2017)
  2. Permenter, Frank; Friberg, Henrik A.; Andersen, Erling D.: Solving conic optimization problems via self-dual embedding and facial reduction: A unified approach (2017)
  3. Kevin K. H. Cheung, Ambros Gleixner, Daniel E. Steffy: Verifying Integer Programming Results (2016) arXiv
  4. Klep, Igor; Povh, Janez: Constrained trace-optimization of polynomials in freely noncommuting variables (2016)
  5. Ku, Wen-Yang; Beck, J.Christopher: Mixed integer programming models for job shop scheduling: A computational analysis (2016)
  6. O’Donoghue, Brendan; Chu, Eric; Parikh, Neal; Boyd, Stephen: Conic optimization via operator splitting and homogeneous self-dual embedding (2016)
  7. Santos, Haroldo G.; Toffolo, Túlio A.M.; Gomes, Rafael A.M.; Ribas, Sabir: Integer programming techniques for the nurse rostering problem (2016)
  8. Lubin, Miles; Dunning, Iain: Computing in operations research using Julia (2015)
  9. Mamalis, Basilis; Pantziou, Grammati: Advances in the parallelization of the simplex method (2015)
  10. Berthold, Timo: RENS. The optimal rounding (2014)
  11. Bussieck, Michael R.; Dirkse, Steven P.; Vigerske, Stefan: PAVER 2.0: an open source environment for automated performance analysis of benchmarking data (2014)
  12. Domes, Ferenc; Fuchs, Martin; Schichl, Hermann; Neumaier, Arnold: The optimization test environment (2014)
  13. Rui, Shaoping; Xu, Chengxian: An inexact smoothing method for SOCCPs based on a one-parametric class of smoothing function (2014)
  14. Tatsumi, Keiji; Tanino, Tetsuzo: Support vector machines maximizing geometric margins for multi-class classification (2014)
  15. Berthold, Timo: Measuring the impact of primal heuristics (2013)
  16. Burgdorf, Sabine; Cafuta, Kristijan; Klep, Igor; Povh, Janez: The tracial moment problem and trace-optimization of polynomials (2013)
  17. Burgdorf, Sabine; Cafuta, Kristijan; Klep, Igor; Povh, Janez: Algorithmic aspects of sums of Hermitian squares of noncommutative polynomials (2013)
  18. Chvátal, Vašek; Cook, William; Espinoza, Daniel: Local cuts for mixed-integer programming (2013)
  19. Cook, William; Koch, Thorsten; Steffy, Daniel E.; Wolter, Kati: A hybrid branch-and-bound approach for exact rational mixed-integer programming (2013)
  20. Kristiansen, Simon; Sørensen, Matias; Herold, Michael B.; Stidsen, Thomas R.: The consultation timetabling problem at Danish high schools (2013)

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