XPRESS

FICO Xpress is the premier mathematical modeling and optimization software suite in the world, with the best tools available to aid the development and deployment of optimization applications that solve real-world challenges. FICO Xpress helps organizations solve bigger problems, design applications faster and make even better decisions in virtually any business scenario. Xpress Optimization Suite includes two types of tools: model building and development tools, and solver engines.


References in zbMATH (referenced in 119 articles )

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  1. Berthold, Timo; Farmer, James; Heinz, Stefan; Perregaard, Michael: Parallelization of the FICO Xpress-Optimizer (2016)
  2. Borndörfer, Ralf; Schenker, Sebastian; Skutella, Martin; Strunk, Timo: PolySCIP (2016)
  3. Buchheim, Christoph; De Santis, Marianna; Lucidi, Stefano; Rinaldi, Francesco; Trieu, Long: A feasible active set method with reoptimization for convex quadratic mixed-integer programming (2016)
  4. Cire, Andre A.; Hooker, John N.; Yunes, Tallys: Modeling with metaconstraints and semantic typing of variables (2016)
  5. Fischetti, Matteo; Lodi, Andrea; Monaci, Michele; Salvagnin, Domenico; Tramontani, Andrea: Improving branch-and-cut performance by random sampling (2016)
  6. Friberg, Henrik A.: CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization (2016)
  7. Greuel, Gert-Martin (ed.); Koch, Thorsten (ed.); Paule, Peter (ed.); Sommese, Andrew (ed.): Mathematical software -- ICMS 2016. 5th international conference, Berlin, Germany, July 11--14, 2016. Proceedings (2016)
  8. Kumbartzky, Nadine; Werners, Brigitte: Optimising energy procurement for small and medium-sized enterprises (2016)
  9. Schilling, Andreas; Werners, Brigitte: Optimizing information security investments with limited budget (2016)
  10. Shinano, Yuji; Berthold, Timo; Heinz, Stefan: A first implementation of paraxpress: combining internal and external parallelization to solve MIPs on supercomputers (2016)
  11. Veremyev, Alexander; Prokopyev, Oleg A.; Butenko, Sergiy; Pasiliao, Eduardo L.: Exact MIP-based approaches for finding maximum quasi-cliques and dense subgraphs (2016)
  12. Brahimi, Nadjib; Absi, Nabil; Dauzère-Pérès, Stéphane; Kedad-Sidhoum, Safia: Models and Lagrangian heuristics for a two-level lot-sizing problem with bounded inventory (2015)
  13. Brahimi, Nadjib; Dauzère-Pérès, Stéphane: A Lagrangian heuristic for capacitated single item lot sizing problems (2015)
  14. Dey, Santanu S.; Gupte, Akshay: Analysis of MILP techniques for the pooling problem (2015)
  15. Gunpinar, Serkan; Centeno, Grisselle: Stochastic integer programming models for reducing wastages and shortages of blood products at hospitals (2015)
  16. Hendel, Gregor: Enhancing MIP branching decisions by using the sample variance of pseudo costs (2015)
  17. Lutter, Pascal; Werners, Brigitte: Order acceptance for motorail transportation with uncertain parameters (2015)
  18. Ma, Ding; Saunders, Michael A.: Solving multiscale linear programs using the simplex method in quadruple precision (2015)
  19. Mamalis, Basilis; Pantziou, Grammati: Advances in the parallelization of the simplex method (2015)
  20. Mortenson, Michael J.; Doherty, Neil F.; Robinson, Stewart: Operational research from Taylorism to terabytes: a research agenda for the analytics age (2015)

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