Computing Block-Angular Karmarkar Projections with Applications to Stochastic Programming
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- Kouwenberg, Roy, 2001. "Scenario generation and stochastic programming models for asset liability management," European Journal of Operational Research, Elsevier, vol. 134(2), pages 279-292, October.
- Vladimirou, Hercules, 1998. "Computational assessment of distributed decomposition methods for stochastic linear programs," European Journal of Operational Research, Elsevier, vol. 108(3), pages 653-670, August.
- Gondzio, Jacek, 2012. "Interior point methods 25 years later," European Journal of Operational Research, Elsevier, vol. 218(3), pages 587-601.
- Zhang, S., 2002. "An interior-point and decomposition approach to multiple stage stochastic programming," Econometric Institute Research Papers EI 2002-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Gondzio, J. & Sarkissian, R. & Vial, J.-P., 1997. "Using an interior point method for the master problem in a decomposition approach," European Journal of Operational Research, Elsevier, vol. 101(3), pages 577-587, September.
- Mulvey, John M. & Rosenbaum, Daniel P. & Shetty, Bala, 1997. "Strategic financial risk management and operations research," European Journal of Operational Research, Elsevier, vol. 97(1), pages 1-16, February.
- Berkelaar, A.B. & Dert, C.L. & Oldenkamp, K.P.B. & Zhang, S., 1999. "A primal-dual decomposition based interior point approach to two-stage stochastic linear programming," Econometric Institute Research Papers EI 9918-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- repec:spr:joptap:v:102:y:1999:i:1:d:10.1023_a:1021850714072 is not listed on IDEAS
- Escudero, L. F. & Fuente, J. L. de la & García, C. & Prieto, Francisco J., 1996. "A parallel computation approach for solving multistage stochastic network problems," DES - Working Papers. Statistics and Econometrics. WS 10455, Universidad Carlos III de Madrid. Departamento de Estadística.
- Diana Barro & Elio Canestrelli, 2005. "Time and nodal decomposition with implicit non-anticipativity constraints in dynamic portfolio optimization," GE, Growth, Math methods 0510011, EconWPA.
- Jacek Gondzio & Andreas Grothey, 2009. "Exploiting structure in parallel implementation of interior point methods for optimization," Computational Management Science, Springer, vol. 6(2), pages 135-160, May.
- Emmanuel Fragnière & Jacek Gondzio & Robert Sarkissian & Jean-Philippe Vial, 2000. "A Structure-Exploiting Tool in Algebraic Modeling Languages," Management Science, INFORMS, vol. 46(8), pages 1145-1158, August.
- Meszaros, Csaba, 1997. "The augmented system variant of IPMs in two-stage stochastic linear programming computation," European Journal of Operational Research, Elsevier, vol. 101(2), pages 317-327, September.
- Berkelaar, Arjan & Dert, Cees & Oldenkamp, Bart, 1999. "A primal-dual decompsition-based interior point approach to two-stage stochastic linear programming," Serie Research Memoranda 0026, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
- J. Gondzio, 1994. "Preconditioned Conjugate Gradients in an Interior Point Method for Two-stage Stochastic Programming," Working Papers wp94130, International Institute for Applied Systems Analysis.
- repec:spr:joptap:v:131:y:2006:i:3:d:10.1007_s10957-006-9156-y is not listed on IDEAS
- repec:spr:joptap:v:143:y:2009:i:1:d:10.1007_s10957-009-9555-y is not listed on IDEAS
- Bocanegra, Silvana & Castro, Jordi & Oliveira, Aurelio R.L., 2013. "Improving an interior-point approach for large block-angular problems by hybrid preconditioners," European Journal of Operational Research, Elsevier, vol. 231(2), pages 263-273.
- A. Ruszczynski, 1993. "Interior Point Methods in Stochastic Programming," Working Papers wp93008, International Institute for Applied Systems Analysis.
- Cosmin Petra & Mihai Anitescu, 2012. "A preconditioning technique for Schur complement systems arising in stochastic optimization," Computational Optimization and Applications, Springer, vol. 52(2), pages 315-344, June.
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Keywordslinear programming; stochastic programming; Karmarkar method;
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