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 188 articles , 1 standard article )

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  1. Berthold, Timo; Farmer, James; Heinz, Stefan; Perregaard, Michael: Parallelization of the FICO Xpress-Optimizer (2018)
  2. Berthold, Timo; Hendel, Gregor; Koch, Thorsten: From feasibility to improvement to proof: three phases of solving mixed-integer programs (2018)
  3. Helm, Werner E.; Justkowiak, Jan-Erik: Extension of Mittelmann’s benchmarks: comparing the solvers of SAS and Gurobi (2018)
  4. Huangfu, Q.; Hall, J. A. J.: Parallelizing the dual revised simplex method (2018)
  5. Lancia, Giuseppe; Serafini, Paolo: Compact extended linear programming models (2018)
  6. Pavlikov, Konstantin; Uryasev, Stan: CVaR distance between univariate probability distributions and approximation problems (2018)
  7. Pinto, Bruno Q.; Ribeiro, Celso C.; Rosseti, Isabel; Plastino, Alexandre: A biased random-key genetic algorithm for the maximum quasi-clique problem (2018)
  8. Sáez-Aguado, Jesús; Trandafir, Paula Camelia: Variants of the $\varepsilon$-constraint method for biobjective integer programming problems: application to $p$-median-cover problems (2018)
  9. Shinano, Yuji; Berthold, Timo; Heinz, Stefan: ParaXpress: an experimental extension of the FICO Xpress-Optimizer to solve hard MIPs on supercomputers (2018)
  10. Zhou, Kai; Kılınç, Mustafa R.; Chen, Xi; Sahinidis, Nikolaos V.: An efficient strategy for the activation of MIP relaxations in a multicore global MINLP solver (2018)
  11. Agra, Agostinho; Cerdeira, Jorge Orestes; Requejo, Cristina: A decomposition approach for the $p$-median problem on disconnected graphs (2017)
  12. Balasubramaniam, Chitra; Butenko, Sergiy: On robust clusters of minimum cardinality in networks (2017)
  13. Fernández, Pascual; Pelegrín, Blas; Lančinskas, Algirdas; Žilinskas, Julius: New heuristic algorithms for discrete competitive location problems with binary and partially binary customer behavior (2017)
  14. Fortz, Bernard; Oliveira, Olga; Requejo, Cristina: Compact mixed integer linear programming models to the minimum weighted tree reconstruction problem (2017)
  15. Harbering, Jonas: Delay resistant line planning with a view towards passenger transfers (2017)
  16. Juan F. Pérez; Daniel F. Silva; Julio C. Góez; Andrés Sarmiento; Andrés Sarmiento-Romero; Raha Akhavan-Tabatabaei; Germán Riaño: Algorithm 972: jMarkov: An Integrated Framework for Markov Chain Modeling (2017)
  17. Lima, Ricardo M.; Grossmann, Ignacio E.: On the solution of nonconvex cardinality Boolean quadratic programming problems: a computational study (2017)
  18. Lutter, Pascal; Degel, Dirk; Büsing, Christina; Koster, Arie M. C. A.; Werners, Brigitte: Improved handling of uncertainty and robustness in set covering problems (2017)
  19. Pelegrín, Mercedes; Pelegrín, Blas: Nash equilibria in location games on a network (2017)
  20. Séguin, Sara; Fleten, Stein-Erik; C^oté, Pascal; Pichler, Alois; Audet, Charles: Stochastic short-term hydropower planning with inflow scenario trees (2017)

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