A comparison of anticipatory algorithms for the dynamic and stochastic traveling salesman problem

Transportation Science

Volumn 46, Issue 3, 2012, Pages 374-387

  Ghiani, Gianpaolo ^a   Manni, Emanuele ^a   Thomas, Barrett W ^b  

^a UNIVERSITY OF SALENTO   (Italy)

^b UNIVERSITY OF IOWA   (United States)

Author keywords

Dynamic; Stochastic; Vehicle routing

Indexed keywords

DYNAMICS; STOCHASTIC SYSTEMS; VEHICLE ROUTING;

COMPUTATIONAL EFFORT; ROUTING PROBLEMS; SCENARIO PLANNING; SOLUTION APPROACH; SOLUTION QUALITY; SOLUTION STRUCTURES; STOCHASTIC; STOCHASTIC TRAVELING SALESMAN;

TRAVELING SALESMAN PROBLEM;

EID: 84866344527     PISSN: 00411655     EISSN: 15265447     Source Type: Journal    
DOI: 10.1287/trsc.1110.0374     Document Type: Article

References (40)

1. Aantjes, C. 2010. Personal communication. September 20.
2. Bent, R., P. Van Hentenryck. 2004. Scenario-based planning for partially dynamic vehicle routing with stochastic customers. Oper. Res. 52(6) 977-987. (Pubitemid 40122356)
3. Benton, W. C., M. D. Rossetti. 1992. The vehicle scheduling problem with intermittent customer demands. Comput. Oper. Res. 19(6) 521-531. (Pubitemid 23559632)
4. Branke, J., M. Middendorf, G. Noeth, M. Dessouky. 2005. Waiting strategies for dynamic vehicle routing. Transportation Sci. 39(3) 298-312. (Pubitemid 41344658)
5. Dumas, Y., J. Desrosiers, E. Gelinas, M. M. Solomon. 1995. An optimal algorithm for the traveling salesman problem with time windows. Oper. Res. 43(2) 367-371.
6. Feo, T. A., M. G. C. Resende. 1995. Greedy randomized adpative search procedures. J. Global Optim. 6(2) 109-134.
7. Gendreau, M., F. Guerten, J.-Y. Potvin, É. Taillard. 1999. Parallel tabu search for real-time vehicle routing and dispatching. Transportation Sci. 33(4) 381-390. (Pubitemid 30519518)
8. Ghiani, G., E. Manni, A. Quaranta, C. Triki. 2009. Anticipatory algorithms for same-day courier dispatching. Transportation Res. Part E 45(1) 96-106.
9. Goodson, J., J. W. Ohlmann, B. W. Thomas. 2011. A rollout policy framework for dynamic programming approximations to the vehicle routing problem with stochastic demand and duration limits. Working paper, Tippie College of Business, University of Iowa, Iowa City.
10. Haughton, M. A. 2000. Quantifying the benefits of route reoptimisation under stochastic customer demand. J. Oper. Res. Soc. 51(3) 320-332. (Pubitemid 30566164)
11. Haughton, M. A. 2002. Route reoptimization's impact on delivery efficiency. Transportation Res. - Part E 38(1) 53-63. (Pubitemid 34043315)
12. Hvattum, L. M., A. Løkketangen, G. Laporte. 2006. Solving a dynamic and stochastic vehicle routing problem with a sample scenario hedging heuristic. Transportation Sci. 40(4) 421-438. (Pubitemid 44746133)
13. Ichoua, S., M. Gendreau, J.-Y. Potvin. 2000. Diversion issues in realtime vehicle dispatching. Transportation Sci. 34(4) 426-438. (Pubitemid 32138221)
14. Ichoua, S., M. Gendreau, J.-Y. Potvin. 2006. Exploiting knowledge about future demands for real-time vehicle dispatching. Transportation Sci. 40(2) 211-225.
15. Kantor, M. G., M. B. Rosenwein. 1992. The orienteering problem with time windows. J. Oper. Res. Soc. 43(6) 629-635.
16. Kilby, P., P. Prosser, P. Shaw. 1998. Dynamic VRPs: A study of scenarios. Technical report APES-06-1998, Department of Computer Science, University of Strathclyde, Glasgow, UK.
17. Larsen, A., O. B. G. Madsen, M. M. Solomon. 2002. Partially dynamic vehicle routing - Models and algorithms. J. Oper. Res. Soc. 53(6) 637-646. (Pubitemid 34658252)
18. Larsen, A., O. B. G. Madsen, M. M. Solomon. 2004. The a-priori dynamic traveling salesman problem with time windows. Transportation Sci. 38(4) 459-472.
19. Law, A. M., W. D. Kelton. 2000. Simulation Modeling and Analysis, 3rd ed. McGraw-Hill, Boston.
20. Manni, E. 2007. Topics in real-time fleet management. Ph.D. thesis, Università della Calabria, Arcavacata di Rende, Italy.
21. Manni, E., J. W. Ohlmann, B. W. Thomas. 2009. Variable neighborhood search with scheduled penalty. Working paper, University of Iowa.
22. Meisel, S., U. Suppa, D. Mattfeld. 2011. GRASP based approximate dynamic programming for dynamic routing of a vehicle. S. Voss, M. Caserta, eds. Proc. MIC 2009: The VIII Metaheuristics Internat. Conf., Springer-Verlag, Berlin. Forthcoming.
23. Mitrović-Minić, S., G. Laporte. 2004. Waiting strategies for the dynamic pickup and delivery problem with time windows. Transportation Res. Part B 38(7) 635-655. (Pubitemid 38700071)
24. Mitrović-Minić, S., R. Krishnamurti, G. Laporte. 2004. Doublehorizon based heurisitcs for the dynamic pickup and delivery problem with time windows. Transportation Res. Part B 38(8) 669-685. (Pubitemid 38763499)
25. Nahmias, S. 2001. Production and Operations Analysis, 4th ed. Irwin/McGraw-Hill, Boston.
26. Ohlmann, J. W., B. W. Thomas. 2007. A compressed annealing approach to the traveling salesman problem with time windows. INFORMS J. Comput. 19(1) 80-90.
27. Powell, W. B., P. Jaillet, A. Odoni. 1995. Stochastic and dynamic networks and routing. M. O. Ball, T. L. Magnanti, C. L. Monma, G. L. Nemhauser, eds. Network Routing, Handbooks in Operations Research and Management Science, Vol. 8. Elsevier Science, Amsterdam, 141-295.
28. Psaraftis, H. N. 1988. Dynamic vehicle routing problems. B. L. Golden, A. A. Assad, eds. Vehicle Routing: Methods and Studies. North-Holland, Amsterdam, 223-248.
29. Psaraftis, H. N. 1995. Dynamic vehicle routing: Status and prospects. Ann. Oper. Res. 61(1) 143-164. (Pubitemid 126016685)
30. Savelsbergh, M. W. P., M. Goetschalckx. 1995. A comparison of the efficiency of fixed versus variable vehicle routes. J. Bus. Logist. 16(1) 163-187.
31. Secomandi, N. 2000. Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands. Comput. Oper. Res. 27(11-12) 1201-1225. (Pubitemid 30398145)
32. Secomandi, N. 2001. A rollout policy for the vehicle routing policy with stochastic demands. Oper. Res. 49(5) 796-802. (Pubitemid 34011330)
33. Secomandi, N., F. Margot. 2009. Reoptimization approaches for the vehicle-routing problem with stochastic demands. Oper. Res. 57(1) 214-230.
34. Solomon, M. M. 1987. Algorithms for the vehicle routing and scheduling problems with time windows. Oper. Res. 35(2) 254-265.
35. Stefik, M. 1981. Planning with constraints (MOLGEN: Part 1). Artificial Intelligence 16(2) 111-139.
36. Thomas, B. W. 2007. Waiting strategies for anticipating service requests from known customer locations. Transportation Sci. 41(3) 319-331.
37. van de Klundert, J., L. Wormer. 2010. ASAP: The aftersalesman problem. Manufacturing Service Oper. Management 12(4) 627-641.
38. van Hemert, J. I., J. A. La Poutré. 2004. Dynamic routing problems with fruitful regions: Models and evolutionary computation.
39. X. Yao, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo-Guervós, J. A. Bullinaria, J. Rowe, P. Tino, A. Kabán, H.-P. Schwefel, eds. Parallel Problem Solving from Nature VIII. Springer-Verlag, Berlin, 692-701.
40. Waters, C. D. J. 1989. Vehicle scheduling problems with uncertainty and omitted customers. J. Oper. Res. Soc. 40(2) 1099-1108.