OSL

Implementing interior point linear programming methods in the Optimization Subroutine Library. This paper discusses the implementation of interior point (barrier) methods for linear programming within the framework of the IBM Optimization Subroutine Library. This class of methods uses quite different computational kernels than the traditional simplex method. In particular, the matrices we must deal with are symmetric and, although still sparse, are considerably denser than those assumed in simplex implementations. Severe rank deficiency must also be accommodated, making it difficult to use off-the-shelf library routines. These features have particular implications for the exploitation of the newer IBM machine architectural features. In particular, interior methods can benefit greatly from use of vector architectures on the IBM $3090^{TM}$ series computers and “super-scalar” processing on the RISC System/$6000^{TM}$ series.


References in zbMATH (referenced in 80 articles )

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  1. Gould, Nicholas I.M.; Orban, Dominique; Toint, Philippe L.: CUTEst: a constrained and unconstrained testing environment with safe threads for mathematical optimization (2015)
  2. Liao, Chao-Ning; Önal, Hayri; Chen, Ming-Hsiang: Average shadow price and equilibrium price: a case study of tradable pollution permit markets (2009)
  3. Xia, Yu: A global optimization method for semi-supervised clustering (2009)
  4. Boschetti, M.A.; Mingozzi, A.; Ricciardelli, S.: A dual ascent procedure for the set partitioning problem (2008)
  5. Zeng, Liangzhao; Ngu, Anne H.H.; Benatallah, Boualem; Podorozhny, Rodion; Lei, Hui: Dynamic composition and optimization of web services (2008)
  6. Peters, Emmanuel; De Matta, Renato; Boe, Warren: Short-term work scheduling with job assignment flexibility for a multi-fleet transport system (2007)
  7. Sylva, John; Crema, Alejandro: A method for finding well-dispersed subsets of non-dominated vectors for multiple objective mixed integer linear programs (2007)
  8. Thompson, Gary M.; Pullman, Madeleine E.: Scheduling workforce relief breaks in advance versus in real-time (2007)
  9. Fréville, Arnaud; Hanafi, Saïd: The multidimensional 0-1 knapsack problem -- bounds and computational aspects (2005)
  10. Fügenschuh, Armin; Martin, Alexander: Computational integer programming and cutting planes (2005)
  11. Ladanyi, Laszlo; Lee, Jon; Lougee-Heimer, Robin: Rapid prototyping of optimization algorithms using COIN-OR: a case study involving the cutting-stock problem (2005)
  12. Quintero, José Luis; Crema, Alejandro: An algorithm for multiparametric min max 0-1-integer programming problems relative to the objective function (2005)
  13. Tsodikov, Yu.M.; Tsodikova, Ya.Yu.: Regularizing functions in many-period production optimization models (2005)
  14. Fréville, Arnaud: The multidimensional 0-1 knapsack problem: an overview. (2004)
  15. Sylva, John; Crema, Alejandro: A method for finding the set of non-dominated vectors for multiple objective integer linear programs (2004)
  16. Wilhelm, Wilbert E.; Gadidov, Radu: A branch-and-cut approach for a generic multiple-product, assembly-system design problem (2004)
  17. Barahona, Francisco; Anbil, Ranga: On some difficult linear programs coming from set partitioning (2002)
  18. Crema, Alejandro: An algorithm to perform a complete parametric analysis relative to the constraint matrix for a 0-1-integer linear program (2002)
  19. Joseph, Anito: A concurrent processing framework for the set partitioning problem (2002)
  20. Júdice, Joaquim J.; Faustino, Ana M.; Ribeiro, Isabel Martins: On the solution of NP-hard linear complementarity problems (2002)

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