Dynamic-Programming Approximations for Stochastic Time-Staged Integer Multicommodity-Flow Problems

Published Online:https://doi.org/10.1287/ijoc.1040.0079

References

  • Aneja Y. P., Nair K. P. Multicommodity network flows with probabilistic loses. Management Sci. (1982) 28:1080–1086LinkGoogle Scholar
  • Assad A. A. Multicommodity network flows—A survey. Networks (1978) 8:37–91CrossrefGoogle Scholar
  • Bellman R.Dynamic Programming (1957) (Princeton University Press, Princeton, NJ) Google Scholar
  • Bertsekas D., Tsitsiklis J.Neuro-Dynamic Programming (1996) (Athena Scientific, Belmont, MA) Google Scholar
  • Chen Z.-L., Powell W. B. A convergent cutting-plane and partial-sampling algorithm for multistage linear programs with recourse. J. Optim. Theory Appl. (1999) 103:497–524CrossrefGoogle Scholar
  • Chih K.-K. A real time dynamic optimal freight car management simulation model of the multiple railroad, multicommodity temporal spatial network flow problem. (1986) . Ph.D. thesis, Department of Civil Engineering and Operations Research, Princeton University, Princeton, NJGoogle Scholar
  • Crainic T. G., Gendreau M., Dejax P. Dynamic and stochastic models for the allocation of empty containers. Oper. Res. (1993) 41:102–126LinkGoogle Scholar
  • Godfrey G. A., Powell W. B. An adaptive, dynamic programming algorithm for stochastic resource allocation problems I: Single period travel times. Transportation Sci. (2002) 36:21–39LinkGoogle Scholar
  • Hane C., Barnhart C., Johnson E., Marsten R., Nemhauser G., Sigismondi G. The fleet assignment problem: Solving a large-scale integer program. Math. Programming (1995) 70:211–232CrossrefGoogle Scholar
  • Haneveld W. K. K., van der Vlerk M. H. Stochastic integer programming: General models and algorithms. Ann. Oper. Res. (1999) 85:39–57CrossrefGoogle Scholar
  • Higle J., Sen S. Stochastic decomposition: An algorithm for two stage linear programs with recourse. Math. Oper. Res. (1991) 16:650–669LinkGoogle Scholar
  • Holmberg K., Joborn M., Lundgren J. T. Improved empty freight car distribution. Transportation Sci. (1998) 32:163–173LinkGoogle Scholar
  • Jordan W., Turnquist M. A stochastic dynamic network model for railroad car distribution. Transportation Sci. (1983) 17:123–145LinkGoogle Scholar
  • Kennington J. L. A survey of linear cost multicommodity network flows. Oper. Res. (1978) 26:209–236LinkGoogle Scholar
  • Powell W. B. A review of sensitivity results for linear networks and a new approximation to reduce the effects of degeneracy. Transportation Sci. (1989) 23:231–243LinkGoogle Scholar
  • Powell W. B., Carvalho T. A. Dynamic control of logistics queueing network for large-scale fleet management. Transportation Sci. (1998) 32:90–109LinkGoogle Scholar
  • Powell W. B., Jaillet P., Odoni A., Ball M. O., Magnanti T. L., Monma C. L., Nemhauser G. L. Stochastic and dynamic networks and routing. Network Routing, Handbooks in Operations Research and Management Science (1995) Vol. 8(North-Holland, Amsterdam, The Netherlands) 141–295Google Scholar
  • Powell W. B., Ruszczynski A., Topaloglu H. Learning algorithms for separable approximations of discrete stochastic optimization problems. Math. Oper. Res. (2004) 29:814–836LinkGoogle Scholar
  • Shan Y. A dynamic multicommodity network flow model for real-time optimal rail freight car management. (1985) . Ph.D. thesis, Department of Civil Engineering and Operations Research, Princeton University, Princeton, NJGoogle Scholar
  • Soroush H. P., Mirchandani B. The stochastic multicommodity flow problem. Networks (1990) 20:121–155CrossrefGoogle 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.