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The Impact of Metaheuristics on Solving the Vehicle Routing Problem: Algorithms, Problem Sets, and Computational Results

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Fleet Management and Logistics

Part of the book series: Centre for Research on Transportation ((CRT))

Abstract

In the standard, capacitated vehicle routing problem (VRP), a homogeneous fleet of vehicles services a set of customers from a single depot. Each vehicle has a fixed capacity that cannot be exceeded and each customer has a known demand that must be satisfied. Each customer must be serviced by exactly one visit of a single vehicle and each vehicle must leave and return to the depot. There may be route-length restrictions that limit the distance traveled by each vehicle. The objective is to generate a sequence of deliveries for each vehicle so that all customers are serviced and the total distance traveled by the fleet is minimized.

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References

  • Alfa, A., S. Heragu and M. Chen. (1991). A 3-opt Based Simulated Annealing Algorithm for Vehicle Routing Problems. Computers & Industrial Engineering, 21(1-4), 635–639.

    Article  Google Scholar 

  • Ball, M., T. Magnanti, C. Monma and G. Nemhauser (editors). (1995). Network Routing. Handbooks in Operations Research and Management Science, Volume 8, El-sevier, Amsterdam, The Netherlands.

    Google Scholar 

  • Beasley, J. (1990). OR-Library: Distributing Test Problems by Electronic Mail, Journal of the Operational Research Society, 41(11), 1069–1072.

    Google Scholar 

  • Bodin, L., B. Golden, A. Assad and M. Ball. (1983). Routing and Scheduling of Vehicles and Crews. Computers & Operations Research, 10(2), 63–211.

    Article  Google Scholar 

  • Chao, I-M., B. Golden and E. Wasil. (1993). A New Heuristic for the Multi-depot Vehicle Routing Problem that Improves Upon Best-known Solutions. American Journal of Mathematical and Management Sciences, 13(3 & 4), 371–406.

    Article  Google Scholar 

  • Chao, I-M., B. Golden and E. Wasil. (1995). An Improved Heuristic for the Period Vehicle Routing Problem. Networks, 26, 25–44.

    Article  Google Scholar 

  • Christofides, N. and S. Eilon. (1969). An Algorithm for the Vehicle Dispatching Problem. Operational Research Quarterly, 20, 309–318.

    Article  Google Scholar 

  • Christofides, N., A. Mingozzi and P. Toth. (1979). The Vehicle Routing Problem. In N. Christofides, A. Mingozzi, P. Toth, and C. Sandi, editors, Combinatorial Optimization, pages 315–338, John Wiley & Sons, Chichester, UK.

    Google Scholar 

  • Clarke, G. and J. Wright. (1964). Scheduling of Vehicles from a Central Depot to a Number of Delivery Points. Operations Research, 12, 568–581.

    Article  Google Scholar 

  • Cullen, F., J. Jarvis and D. Ratliff. (1981). Set Partitioning Based Heuristics for Interactive Routing. Networks, 11, 125–144.

    Article  Google Scholar 

  • Dantzig, G. and J. Ramser. (1959). The Truck Dispatching Problem. Management Science, 6, 81–91.

    Google Scholar 

  • Dueck, G. (1993). New Optimization Heuristics: The Great Deluge Algorithm and the Record-to-Record Travel. Journal of Computational Physics, 104, 86–92.

    Article  Google Scholar 

  • Dueck, G. and T. Scheurer. (1990). Threshold Accepting: A General Purpose Optimization Algorithm. Journal of Computational Physics, 90, 161–175.

    Article  Google Scholar 

  • Fisher, M. (1994). Optimal Solution of Vehicle Routing Problems Using Minimum K-Trees. Operations Research, 42, 626–642.

    Article  Google Scholar 

  • Fisher, M. (1995). Vehicle Routing. In M. Ball, T. Magnanti, C. Monma, and G. Nemhauser, editors, Network Routing, Handbooks in Operations Research and Management Science, Volume 8, pages 1–33, Elsevier, Amsterdam, The Netherlands.

    Google Scholar 

  • Fisher, M. and R. Jaikumar. (1981). A Generalized Assignment Heuristic for Vehicle Routing. Networks, 11, 109–124.

    Article  Google Scholar 

  • Gendreau, M., A. Hertz and G. Laporte. (1991). A Tabu Search Heuristic for the Vehicle Routing Problem. CRT-777, Centre de Recherche sur les Transports, Université de Montréal, Montréal, Canada.

    Google Scholar 

  • Gendreau, M., A. Hertz and G. Laporte. (1994). A Tabu Search Heuristic for the Vehicle Routing Problem. Management Science, 40, 1276–1290.

    Article  Google Scholar 

  • Gendreau, M., G. Laporte and J-Y. Potvin. (1997). Vehicle Routing: Modern Heuristics. In E. Aarts and J.K. Lenstra, editors, Local Search in Combinatorial Optimization, pages 311–336, John Wiley & Sons Ltd., London, England.

    Google Scholar 

  • Ghaziri, H. (1996). Supervision in the Self-organizing Feature Map: Application to the Vehicle Routing Problem, In I. Osman and J. Kelly, editors, Meta-heuristics: Theory and Applications, pages 651–660, Kluwer Academic Publishers, Boston, Massachusetts.

    Chapter  Google Scholar 

  • Gillett, B. and L. Miller. (1974). A Heuristic Algorithm for the Vehicle Dispatch Problem. Operations Research, 22, 340–349.

    Article  Google Scholar 

  • Glover, F. (1997). Tabu Search and Adaptive Memory Programming — Advances, Applications and Challenges, In R. Barr, R. Helgason and J. Kennington, editors, Interfaces in Computer Science and Operations Research: Advances in Metaheuristics, Optimization, and Stochastic Modeling Technologies, pages 1–75, Kluwer Academic Publishers, Boston, Massachusetts.

    Chapter  Google Scholar 

  • Golden, B. and A. Assad (editors). (1988). Vehicle Routing: Methods and Studies. Studies in Management Science and Systems, Volume 16, North-Holland, Amsterdam, The Netherlands.

    Google Scholar 

  • Golden, B., T. Magnanti and H. Nguyen. (1997). Implementing Vehicle Routing Algorithms. Networks, 7, 113–148.

    Article  Google Scholar 

  • Hall, R. and J. Partyka. (1997). On the Road to Efficiency. OR/MS Today, 24(3), 38–47.

    Google Scholar 

  • Laporte, G. (1992). The Vehicle Routing Problem: An Overview of Exact and Approximate Algorithms. European Journal of Operational Research, 59, 345–358.

    Article  Google Scholar 

  • Osman, I. (1993). Metastrategy Simulated Annealing and Tabu Search Algorithms for the Vehicle Routing Problem. Annals of Operations Research, 41, 421–451.

    Article  Google Scholar 

  • Osman, I. and J. Kelly. (1996). Meta-heuristics: An Overview. In I. Osman and J. Kelly, editors, Meta-heuristics: Theory and Applications, pages 1–21, Kluwer Academic Publishers, Boston, Massachusetts.

    Chapter  Google Scholar 

  • Reeves, C. (editor). (1993). Modern Heuristic Techniques for Combinatorial Problems. Halsted Press, New York.

    Google Scholar 

  • Rego, C. and C. Roucairol. (1996). A Parallel Tabu Search Algorithm Using Ejection Chains for the Vehicle Routing Problem, in Meta-heuristics: Theory and Applications, edited by I. Osman and J. Kelly, 661–675, Kluwer Academic Publishers, Boston, Massachusetts.

    Chapter  Google Scholar 

  • Robertson, S., B. Golden, G. Runger and E. Wasil. (1998). Neural Network Models for Initial Public Offerings, forthcoming in Neurocomputing.

    Google Scholar 

  • Robusté, F., C. Daganzo and R. Souleyrette II. (1990). Implementing Vehicle Routing Models. Transportation Research, 24B(4), 263–286.

    Article  Google Scholar 

  • Rochat, Y. and E. Taillard. (1995). Probabilistic Diversification and Intensification in Local Search for Vehicle Routing. Journal of Heuristics, 1, 147–167.

    Article  Google Scholar 

  • Russell, R. (1977). An Effective Heuristic for the M-Tour Traveling Salesman Problem with Some Side Conditions. Operations Research, 25, 517–524.

    Article  Google Scholar 

  • Semet, F. and E. Taillard. (1993). Solving Real-life Vehicle Routing Problems Efficiently Using Tabu Search. Annals of Operations Research, 41, 469–488.

    Article  Google Scholar 

  • Taillard, E. (1992). Parallel Iterative Search Methods for Vehicle Routing Problem. ORWP 92/03, École Polytechnique Fédérale de Lausanne, Département de Mathématiques, CH-1015, Lausanne, Switzerland.

    Google Scholar 

  • Taillard, E. (1993). Parallel Iterative Search Methods for Vehicle Routing Problems. Networks, 23, 661–673.

    Article  Google Scholar 

  • Van Breedam, A. (1994). An Analysis of the Behavior of Heuristics for the Vehicle Routing Problem for a Selection of Problems with Vehicle-related, Customer-related, and Time-related Constraints. Ph.D. Dissertation, Faculty of Applied Economics, University of Antwerp — RUCA, Antwerp, Belgium.

    Google Scholar 

  • Van Breedam, A. (1995). Improvement Heuristics for the Vehicle Routing Problem Based on Simulated Annealing. European Journal of Operational Research, 86, 480–490.

    Article  Google Scholar 

  • Van Breedam, A. (1996). An Analysis of the Effect of Local Improvement Operators in Genetic Algorithms and Simulated Annealing for the Vehicle Routing Problem. RUCA Working Paper 96/14, Faculty of Applied Economics, University of Antwerp, Antwerp, Belgium.

    Google Scholar 

  • Xu, J., S. Chiu and F. Glover. (1996). Fine-tuning a Tabu Search Algorithm with Statistical Tests. Working Paper, Graduate School of Business, University of Colorado, Boulder, Colorado.

    Google Scholar 

  • Xu, J. and J. Kelly. (1996). A Network Flow-Based Tabu Search Heuristic for the Vehicle Routing Problem. Transportation Science, 30, 379–393.

    Article  Google Scholar 

  • Xu, J. and J. Kelly. (1997). Personal communication.

    Google Scholar 

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Authors
  1. Bruce L. Golden
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  2. Edward A. Wasil
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  3. James P. Kelly
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  4. I-Ming Chao
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Editor information

Editors and Affiliations

  1. Université du Québec à Montréal, Canada

    Teodor Gabriel Crainic

  2. École des Hautes Études Commerciales de Montréal, Canada

    Gilbert Laporte

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© 1998 Springer Science+Business Media New York

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Golden, B.L., Wasil, E.A., Kelly, J.P., Chao, IM. (1998). The Impact of Metaheuristics on Solving the Vehicle Routing Problem: Algorithms, Problem Sets, and Computational Results. In: Crainic, T.G., Laporte, G. (eds) Fleet Management and Logistics. Centre for Research on Transportation. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5755-5_2

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  • DOI: https://doi.org/10.1007/978-1-4615-5755-5_2

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7637-8

  • Online ISBN: 978-1-4615-5755-5

  • eBook Packages: Springer Book Archive

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