StAMPL: A Filtration-Oriented Modeling Tool for Multistage Stochastic Recourse Problems

Published Online:https://doi.org/10.1287/ijoc.1080.0289

References

  • Ariyawansa K. A., Felt A. J. On a new collection of stochastic linear programming test problems. INFORMS J. Comput. (2004) 16(3):291–299LinkGoogle Scholar
  • Birge J. R., Louveaux F.Introduction to Stochastic Programming (1997) (Springer-Verlag, New York) Google Scholar
  • Birge J., Dempster M., Gassmann H., Gunn E., King A., Wallace S. A standard input format for multiperiod stochastic linear programs. COAL Newsletter (1987) 17:1–19Google Scholar
  • Bisschop J.AIMMS-Optimization Modeling (2006) (Lulu Press, Inc., Haarlem, The Netherlands) Google Scholar
  • Brooke A., Kendrick D., Meeraus A.GAMS A User's Guide (1988) (The Scientific Press, Redwood City, CA) Google Scholar
  • Buchanan C. S., McKinnon K. I. M., Skondras G. K. The recursive definition of stochastic linear programming problems within an algebraic modeling language. Ann. Oper. Res. (2001) 104:15–32CrossrefGoogle Scholar
  • Collaud G., Pasquier-Boltuck J. gLPS: A graphical tool for the definition and manipulation of linear problems. Eur. J. Oper. Res. (1994) 72:277–268CrossrefGoogle Scholar
  • Condevaux-Lanloy C., Fragnière E., King A. SISP, simplified interface for stochastic programming: Establishing a hard link between mathematical programming modeling languages and SMPS codes. Optim. Methods Software (2002) 17(Special Issue):423–443CrossrefGoogle Scholar
  • Czyzyk J., Mesnier M. P., Moré J. J. The NEOS server. IEEE Comput. Sci. Engrg. (1998) 5:68–75CrossrefGoogle Scholar
  • Dempster M. A. H., Medova E. A., Scott J. E. A modelling system for stochastic programming. (1999) Presentation, OR41September 14Edinburgh, Scotland(Operational Research Society, Birmingham, UK) Google Scholar
  • Dempster M. A. H., Scott J. E., Thompson G. W. P., Wallace S., Ziemba W. Stochastic modelling and optimization using STOCHASTICS. Applications of Stochastic Programming (2005) (Society for Industrial and Applied Mathematics, Philadelphia) 137–158MPS-SIAM Series in OptimizationChapter 9CrossrefGoogle Scholar
  • Dormer A., Vazacopoulos A., Verma N., Tipi H., Geunes J., Pardalos P. Modeling and solving stochastic programming problems in supply chain management using Xpress-SP. Supply Chain Optimization, Applied Optimization (2005) 98(Springer, Boston) 307–354Chapter 10CrossrefGoogle Scholar
  • Ellison F., Mitra G., Poojari C. FortSP: A stochastic programming solver. (2002) . User's manual, OptiRisk Systems, Uxbridge, Middlesex, UKGoogle Scholar
  • Entriken R. Language constructs for modeling stochastic linear programs. Ann. Oper. Res. (2001) 101:49–66CrossrefGoogle Scholar
  • Fleten S.-E., Wallace S. W., Ziemba W. T., Greengard C., Ruszczyński A. Hedging electricity portfolios via stochastic programming. Decision Making Under Uncertainty—Energy and Power. The IMA Volumes in Mathematics and Its Applications (2002) 128(Springer-Verlag, New York) 71–93CrossrefGoogle Scholar
  • Fourer R., Gay D. M. Proposals for stochastic programming in the AMPL modeling language. Internat. Sympos. Math. Programming (1997) . http://users.iems.northwestern.edu/∼4er/SLIDES/#lsn9708Google Scholar
  • Fourer R., Lopes L. A management system for decompositions in stochastic programming. Ann. Oper. Res. (2006) 142:99–118CrossrefGoogle Scholar
  • Fourer R., Gay D. M., Kernighan B. W. A modeling language for mathematical programming. Management Sci. (1990) 36(5):519–554LinkGoogle Scholar
  • Fourer R., Gay D. M., Kernighan B. W.AMPL: A Modeling Language for Mathematical Programming (2002) (Duxbury Press, Brooks/Cole Publishing, Pacific Grove, CA) Google Scholar
  • GAMS Development Corporation OSL stochastic extensions. (2005) . http://www.gams.com/solvers/oslse.pdfGoogle Scholar
  • Gassmann H. I. MSLiP: A computer code for the multistage stochastic linear programming problem. Math. Programming (1990) 47:407–423CrossrefGoogle Scholar
  • Gassmann H. I., Ireland A. M. Scenario formulation in an algebraic modelling language. Ann. Oper. Res. (1995) 59:45–75CrossrefGoogle Scholar
  • Gassmann H. I., Ireland A. M. On the formulation of stochastic linear programs using algebraic modelling languages. Ann. Oper. Res. (1996) 64:83–112CrossrefGoogle Scholar
  • Gassmann H. I., Schweitzer E. A comprehensive input format for stochastic linear programs. Ann. Oper. Res. (2001) 104:89–125CrossrefGoogle Scholar
  • Gay D. M. Hooking your solver to AMPL. (1997) . Technical report, Bell Laboratories, Murray Hill, NJ, http://www.ampl.com/hooking.htmlGoogle Scholar
  • Higle J., Sen S. Stochastic decomposition: An algorithm for two-stage linear programs with recourse. Math. Oper. Res. (1991) 16:650–669LinkGoogle Scholar
  • Infanger G. GAMS/DECIS User's Guide. (1999) . http://www1.gams.com/docs/solver/decis.pdfGoogle Scholar
  • Kall P., Mayer J. SLP-IOR: An interactive model management system for stochastic linear programs. Math. Programming (1996) 75:221–240CrossrefGoogle Scholar
  • King A. J.SP/OSL V1.0, Stochastic Programming Interface Library, User's Guide (1994) (IBM T. J. Watson Research Center, Yorktown Heights, NY) Google Scholar
  • King A. J. The stochastic modeling interface. (2007) . http://projects.coin-or.org/SmiGoogle Scholar
  • Klaassen P. Financial asset-pricing theory and stochastic programming models for asset/liability management: A synthesis. Management Sci. (1998) 44(1):31–48LinkGoogle Scholar
  • Klaassen P., Shapiro J. F., Spitz D. E. Sequential decision models for selecting currency options. (1990) . Technical Report 133-90, International Financial Services Research Center, MIT, Cambridge, MAGoogle Scholar
  • Knuth D. E. Literate programming. Comput. J. (1984) 27:97–111CrossrefGoogle Scholar
  • Kristjansson B.MPL User Manual (2005) (Maximal Software, Inc., Arlington, VA) Google Scholar
  • Ma P., Murphy F. H., Stohr E. A. An implementation of LPFORM. INFORMS J. Comput. (1996) 8:383–401LinkGoogle Scholar
  • Messina E., Mitra G. Modelling and analysis of multistage stochastic programming problems: A software environment. Eur. J. Oper. Res. (1997) 101:343–359CrossrefGoogle Scholar
  • Rockafellar R. T., Wets R. J.-B. Scenarios and policy aggregation in optimization under uncertainty. Math. Oper. Res. (1991) 16:119–147LinkGoogle Scholar
  • Valente P., Mitra G., Poojari C., Kyriakis T., Wallace S. W., Ziemba W. T. A stochastic programming integrated environment. Applications of Stochastic Programming (2005) (Society for Industrial and Applied Mathematics, Philadelphia) 115–136MPS-SIAM Series on OptimizationChapter 8CrossrefGoogle Scholar
  • Valente P., Mitra G., Sadki M., Fourer R. Extending algebraic modelling languages for stochastic programming. (2003) . Technical Report CTR/09/03, CARISMA and Brunel University, Uxbridge, Middlesex, UK, http://hdl.handle.net/2438/767Google Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.