A threshold accepting approach to the Open Vehicle Routing problem

Christos D. Tarantilis; George Ioannou; Chris T. Kiranoudis; Gregory P. Prastacos

RAIRO - Operations Research (2010)

  • Volume: 38, Issue: 4, page 345-360
  • ISSN: 0399-0559

Abstract

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In this paper we consider the operational planning problem of physical distribution via a fleet of hired vehicles, for which the travelling cost is solely a function of the sequence of locations visited within all open delivery routes, while vehicle fixed cost is inexistent. The problem is a special class of vehicle routing and is encountered in the literature as the Open Vehicle Routing Problem (OVRP), since vehicles are not required to return to the depot. The goal is to distribute in an optimal way finished goods from a central facility to geographically dispersed customers, which pose daily demand for items produced in the facility and act as sales points for consumers. To solve the problem, we employ an annealing-based method that utilizes a backtracking policy of the threshold value when no acceptances of feasible solutions occur during the search process. Computational results on a set of benchmark problems show that the proposed method consistently outperforms previous algorithms for solving the OVRP. The approach can serve as the means for effective fleet planning in real-life problems.

How to cite

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Tarantilis, Christos D., et al. "A threshold accepting approach to the Open Vehicle Routing problem." RAIRO - Operations Research 38.4 (2010): 345-360. <http://eudml.org/doc/105319>.

@article{Tarantilis2010,
abstract = { In this paper we consider the operational planning problem of physical distribution via a fleet of hired vehicles, for which the travelling cost is solely a function of the sequence of locations visited within all open delivery routes, while vehicle fixed cost is inexistent. The problem is a special class of vehicle routing and is encountered in the literature as the Open Vehicle Routing Problem (OVRP), since vehicles are not required to return to the depot. The goal is to distribute in an optimal way finished goods from a central facility to geographically dispersed customers, which pose daily demand for items produced in the facility and act as sales points for consumers. To solve the problem, we employ an annealing-based method that utilizes a backtracking policy of the threshold value when no acceptances of feasible solutions occur during the search process. Computational results on a set of benchmark problems show that the proposed method consistently outperforms previous algorithms for solving the OVRP. The approach can serve as the means for effective fleet planning in real-life problems. },
author = {Tarantilis, Christos D., Ioannou, George, Kiranoudis, Chris T., Prastacos, Gregory P.},
journal = {RAIRO - Operations Research},
keywords = {Distribution; vehicle routing; logistics.; logistics},
language = {eng},
month = {3},
number = {4},
pages = {345-360},
publisher = {EDP Sciences},
title = {A threshold accepting approach to the Open Vehicle Routing problem},
url = {http://eudml.org/doc/105319},
volume = {38},
year = {2010},
}

TY - JOUR
AU - Tarantilis, Christos D.
AU - Ioannou, George
AU - Kiranoudis, Chris T.
AU - Prastacos, Gregory P.
TI - A threshold accepting approach to the Open Vehicle Routing problem
JO - RAIRO - Operations Research
DA - 2010/3//
PB - EDP Sciences
VL - 38
IS - 4
SP - 345
EP - 360
AB - In this paper we consider the operational planning problem of physical distribution via a fleet of hired vehicles, for which the travelling cost is solely a function of the sequence of locations visited within all open delivery routes, while vehicle fixed cost is inexistent. The problem is a special class of vehicle routing and is encountered in the literature as the Open Vehicle Routing Problem (OVRP), since vehicles are not required to return to the depot. The goal is to distribute in an optimal way finished goods from a central facility to geographically dispersed customers, which pose daily demand for items produced in the facility and act as sales points for consumers. To solve the problem, we employ an annealing-based method that utilizes a backtracking policy of the threshold value when no acceptances of feasible solutions occur during the search process. Computational results on a set of benchmark problems show that the proposed method consistently outperforms previous algorithms for solving the OVRP. The approach can serve as the means for effective fleet planning in real-life problems.
LA - eng
KW - Distribution; vehicle routing; logistics.; logistics
UR - http://eudml.org/doc/105319
ER -

References

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  1. L. Bodin, B. Golden, A. Assad and M. Ball, Routing and scheduling of vehicles and crews: the state of the art. Comput. Oper. Res.10 (1983) 63–211.  
  2. J. Brandão, A tabu search algorithm for the Open Vehicle Routing Problem. Eur. J. Oper. Res.157 (2004) 552–564.  
  3. O. Bräysy, J. Berger, M. Barkaoui and W. Dullaert, A threshold accepting metaheuristic for the Vehicle Routing Problem with Time Windows. Central Eur. J. Oper. Res.11 (2003) 369–387.  
  4. N. Christofides, A. Mingozzi and P. Toth, The vehicle routing problem, in Combinatorial Optimization, edited by N. Christofides, A. Mingozzi, P. Toth and C. Sandi. Wiley, Chichester (1979) 315–338.  
  5. G. Clarke and J.W. Wright, Scheduling of vehicles from a central depot to a number of delivery points. Oper. Res.12 (1964) 568–589.  
  6. J.-F. Cordeau, M. Gendreau, A. Hertz, G. Laporte and J.S. Sormany, New Heuristics for the Vehicle Routing Problem, in Logistics Systems: Design and Optimization, edited by A. Langevin et D. Riopel. Kluwer (to appear).  
  7. J.-F. Cordeau, M. Gendreau, G. Laporte, J.-Y. Potvin and F. Semet, A guide to vehicle routing heuristics. J. Oper. Res. Soc.53 (2002) 512–522.  
  8. G. Croes, A method for solving traveling salesman problems. Oper. Res.6 (1958) 791–812.  
  9. G. Dueck and T. Scheuer, Threshold accepting: a general purpose algorithm appearing superior to simulated annealing. J. Comput. Phys.90 (1990) 161–175.  
  10. M. Gendreau, A. Hertz and G. Laporte, A tabu search heuristic for the vehicle routing problem. Manage. Sci.40 (1994) 1276–1290.  
  11. M. Gendreau, A. Hertz and G. Laporte, New insertion and postoptimization procedures for the traveling salesman problem. Oper. Res.40 (1992) 1086–1094.  
  12. B.L. Golden, E.A. Wasil, J.P. Kelly and I.-M. Chao, The impact of metaheuristics on solving the vehicle routing problem: Algorithms, problem sets, and computational results, edited by T.G. Crainic and G. Laporte. Fleet Management and Logistics, Kluwer Academic Publishers, Boston (1998) 33–56.  
  13. B. Golden and A.A. Assad, Vehicle Routing: Methods and Studies. Elsevier Science Publishers, Amsterdam (1988).  
  14. S. Kirkpatrick, C.D. Gelatt Jr. and M.P. Vecchi, Optimization by simulated annealing. Science220 (1983) 671–680.  
  15. D. Sariklis and S. Powell, A heuristic method for the open vehicle routing problem. J. Oper. Res. Soc.51 (2000) 564–573.  
  16. M. Syslo, N. Deo and J. Kowaklik, Discrete Optimization Algoritms with Pascal Programs. Prentice Hall, Inc. (1983).  
  17. C.D. Tarantilis, C.T. Kiranoudis and V.S. Vassiliadis, A list based threshold accepting metaheuristic for the heterogeneous fixed fleet vehicle routing problem. J. Oper. Res. Soc.54 (2003) 65–71.  
  18. C.D. Tarantilis and C.T. Kiranoudis, BoneRoute: An adaptive memory-based method for effective fleet management. Ann. Oper. Res.115 (2002) 227–241.  
  19. C.D.J. Waters, A solution procedure for the vehicle scheduling problem based on iterative route improvement. J. Oper. Res. Soc.38 (1987) 833–839.  

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