Abstract
The well-known Vehicle Routing Problem (VRP) has been generalized toward tactical or strategic decision levels of companies but not both. The tactical extension or Periodic VRP (PVRP) plans trips over a multi-period horizon, subject to frequency constraints. The strategic extension or Location-Routing Problem (LRP) tackles location and routing decisions simultaneously as in most distribution systems interdependence between these decisions leads to low-quality solutions if depots are located first, regardless the future routes. Our goal is to combine for the first time the PVRP and LRP into the Periodic LRP or PLRP. A metaheuristic is proposed to solve large size instances of the PLRP. It is based on our Randomized Extended Clarke and Wright Algorithm (RECWA) for the LRP and it tries to take into consideration several decision levels when making a choice during the construction of a solution. The method is evaluated on three sets of instances and results are promising. Solutions are compared to the literature on particular cases such as one-day horizon (LRP) or one available depot (PVRP).
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References
http://neo.lcc.uma.es/radi-aeb/WebVRP/, 2007.
S. Barreto and C. Ferreira and J. Paixão and B. Sousa Santos. Using clustering analysis in a capacitated location-routing problem. European Journal of Operational Research, 179:968–977, 2007.
M. Chao, B.L. Golden, and E. Wasil. An improved heuristic for the periodic vehicle routing pproblem. Networks, 26:25–44, 1995.
N. Christofides and J.E. Beasley. The period routing problem. Networks, 14:237–256, 1984.
G. Clarke and J.W. Wright. Scheduling of vehicles from a central depot to a number of delivery points. Operations Research, 12:568–581, 1964.
J.F. Cordeau, M. Gendreau, and G. Laporte. A tabu search heuristic for periodic and multi-depot vehicle routing problems. Networks, 30:105–119, 1997.
C. Prins, C. Prodhon, and R. Wolfler-Calvo. A memetic algorithm with population management (MA | PM) for the capacitated location-routing problem. In J. Gottlieb and G. R. Raidl, editors, Lecture Notes in Computer Science, volume 3906, pages 183–194. Proceedings of EvoCOP2006 (Evolutionary Computation in Combinatorial Optimization: 6th European Conference, Budapest, Hungary, April 10–12, 2006), Springer, 2006.
C. Prins, C. Prodhon, and R. Wolfler-Calvo. Solving the capacitated location-routing problem by a GRASP complemented by a learning process and a path relinking. 4OR-A Quarterly Journal of Operations Research, 4:221–238, 2006.
C. Prins, C. Prodhon, A. Ruiz, P. Soriano, and R. Wolfler Calvo. Solving the capacitated location-routing problem by a cooperative lagrangean relaxation-granular tabu search heuristic. Transportation Science, 2007.
C. Prodhon. http://prodhonc.free.fr/homepage, 2007.
S. Salhi and G. K. Rand. The effect of ignoring routes when locating depots. European Journal of Operational Research, 39:150–156, 1989.
C.C.R. Tan and J.E. Beasley. A heuristic algorithm for the periodic vehicle routing problem. Omega International Journal of Management Science, 12(5):497–504, 1984.
T.H. Wu, C. Low, and J.W Bai. Heuristic solutions to multi-depot location-routing problems. Computers and Operations Research, 29:1393–1415, 2002.
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© 2008 Springer-Verlag Berlin Heidelberg
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Prodhon, C. (2008). A Metaheuristic for the Periodic Location-Routing Problem. In: Kalcsics, J., Nickel, S. (eds) Operations Research Proceedings 2007. Operations Research Proceedings, vol 2007. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77903-2_25
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DOI: https://doi.org/10.1007/978-3-540-77903-2_25
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