Scenario-Based Planning for Partially Dynamic Vehicle Routing with Stochastic Customers

Published Online:https://doi.org/10.1287/opre.1040.0124

References

  • Ascheuer N., Krumke S., Rambau J. Online dial-a-ride problems: Minimizing the completion time. STACS: 17th Annual Sympos. Theoret. Aspects Comput. Sci. (2000) 639–650Google Scholar
  • Bent R., Van Hentenryck P. A two-stage hybrid local search for the vehicle routing problem with time windows. Transportation Sci. (2004) . ForthcomingLinkGoogle Scholar
  • Bertsimas D. A vehicle routing problem with stochastic demand. Oper. Res. (1992) 40:574–585LinkGoogle Scholar
  • Bertsimas D., van Ryzin G. A stochastic and dynamic vehicle routing problem in the Euclidean plane. Oper. Res. (1991) 39:601–615LinkGoogle Scholar
  • Bertsimas D., van Ryzin G. Stochastic and dynamic vehicle routing in the Euclidean plane with multiple capacitated vehicles. Oper. Res. (1993) 41:60–76LinkGoogle Scholar
  • Bianchi L. Notes of dynamic vehicle routing—The state of the art. (2000) . Technical report IDSIA-05-01, Manno-Lugano, SwitzerlandGoogle Scholar
  • Burckert H., Fischer K., Vierke G. Holonic transport scheduling with Teletruck. Appl. Artificial Intelligence (2000) 14:697–725CrossrefGoogle Scholar
  • Gendreau M., Potvin J. Dynamic vehicle routing and dispatching. (1997) . Technical report CRT 97-38, Centre de Recherche sur les Transport, Universite de Montreal, Montreal, Quebec, CanadaGoogle Scholar
  • Gendreau M., Laporte G., Seguin R. An exact algorithm for the vehicle routing problem with stochastic demands and customers. Transportation Sci. (1995) 29:143–155LinkGoogle Scholar
  • Gendreau M., Laporte G., Seguin R. A tabu search heuristic for the vehicle routing problem with stochastic demands and customers. Oper. Res. (1996a) 44:469–477LinkGoogle Scholar
  • Gendreau M., Laporte G., Seguin R. Stochastic vehicle routing. Eur. J. Oper. Res. (1996b) 88:3–12CrossrefGoogle Scholar
  • Gendreau M., Laporte G., Semet F. A dynamic model and parallel tabu search heuristic for real-time ambulance relocation. Parallel Comput. (2001) 27:1641–1653CrossrefGoogle Scholar
  • Gendreau M., Guertin F., Potvin J., Seguin R. Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries. (1998) . Technical report CRT-98-10, Centre de Recherche sur les Transport, Universite de Montreal, Montreal, Quebec, CanadaGoogle Scholar
  • Gendreau M., Guertin F., Potvin J. Y., Taillard E. Parallel tabu search for real-time vehicle routing and dispatching. Transportation Sci. (1999) 33(4):381–390LinkGoogle Scholar
  • Hauptmeier D., Krumke S., Rambau J. The online dial-a-ride problem under reasonable load. Lecture Notes Comput. Sci. (2000) 1767:125–136CrossrefGoogle Scholar
  • Ichoua S., Gendreau M., Potvin J. Y. Diversion issues in real-time vehicle dispatching. Transporation Sci. (2000) 34:426–438LinkGoogle Scholar
  • Kilby P., Prosser P., Shaw P. Dynamic VRPs: A study of scenarios. (1999) . Technical report APES-06-1998. University of St. Andrews. St. Andrews, ScotlandGoogle Scholar
  • Kindervater G., Savelsbergh M., Aarts E., Lenstra J. K. Vehicle routing: Handling edge exchanges. Local Search in Combinatorial Optimization (1997) (John Wiley and Sons, New York) 337–360Google Scholar
  • Krumke S., Rambau J., Torres L. Real-time dispatching of guided and unguided automobile service units with soft time windows. Proc. 10th Annual Eur. Sympos. on Algorithms (2002) 637–648Rome ItalyCrossrefGoogle Scholar
  • Laporte G., Louveaux F., Mercure H. The vehicle routing problem with stochastic travel times. Transportation Sci. (1992) 26:161–170LinkGoogle Scholar
  • Larsen A. The dynamic vehicle routing problem. (2000) . Ph.D. thesis, Technical University of Denmark, Kongens, Lyngby, DenmarkGoogle Scholar
  • Larsen A., Madsen O., Solomon M. Partially dynamic vehicle routing—Models and algorithms. J. Oper. Res. Soc. (2002) 53:638–646CrossrefGoogle Scholar
  • Lund K., Madsen O., Rygaard J. Vehicle routing problems with varying degrees of dynamism. (1996) . Technical report, IMM. Department of Mathematical Modeling, Technical University of Denmark, Kogens, Lyngby, DenmarkGoogle Scholar
  • Novaes A., Graciolli O. Designing multiple-vehicle delivery tours in a grid-cell format. Eur. J. Oper. Res. (1999) 119:613–634CrossrefGoogle Scholar
  • Powell W. A stochastic formulation of the dynamic assignment problem with an application to truckload motor carriers. Transportation Sci. (1996) 30:195–219LinkGoogle Scholar
  • Powell W., Shapiro J., Simao H. A representational paradigm for dynamic resource transformation problems. Ann. Oper. Res. (2001) 104:231–279CrossrefGoogle Scholar
  • Psaraftis H. Dynamic vehicle routing: Status and prospects. Ann. Oper. Res. (1995) 61:143–164CrossrefGoogle Scholar
  • Savelsbergh M., Sol M. DRIVE: Dynamic routing of independent vehicles. Oper. Res. (1998) 46:474–490LinkGoogle Scholar
  • Secomandi N. Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands. Comput. Oper. Res. (2000) 27:1201–1225CrossrefGoogle Scholar
  • Secomandi N. A rollout policy for the vehicle routing problem with stochastic demands. Oper. Res. (2001) 49:796–802LinkGoogle Scholar
  • Solomon M. M. Algorithms for the vehicle routing and scheduling problems with time window constraints. Oper. Res. (1987) 35(2):254–265LinkGoogle Scholar
  • Stefik M. Planning with constraints (MOLGEN: Part 1). Artificial Intelligence (1981) 16:111–139CrossrefGoogle Scholar
  • Swihart M., Papastavrou J. A stochastic and dynamic model for the single-vehicle pick-up and delivery problem. Eur. J. Oper. Res. (1999) 114:447–464CrossrefGoogle Scholar
  • Yang W., Mathur K., Ballou R. Stochastic vehicle routing problem with restocking. Transportation Sci. (2000) 34:99–112LinkGoogle Scholar
  • Zhu K., Ong K. A reactive method for real time dynamic vehicle routing problem. 12th ICTAI (2000) . Vancouver, British Columbia, CanadaGoogle 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.