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Multi-terminal vehicle-dispatch algorithm

Author

Listed:
  • Gillett, Billy E
  • Johnson, Jerry G

Abstract

This paper introduces the Multi-Terminal Sweep Algorithm, a heuristic algorithm for obtaining an approximate solution to the multiple terminal vehicle-dispatch problem. The procedure determines a set of routes by which vehicles from two or more terminals can service a collection of demand points so that the total distance traveled is kept near to the minimum. This solution also satisfies constraints on the vehicle load and on the length of each route. Application of the algorithm to eleven multiple terminal vehicle-dispatch problems shows that near-optimal solutions to large-scale problems can be found in a reasonable amount of computer time.

Suggested Citation

  • Gillett, Billy E & Johnson, Jerry G, 1976. "Multi-terminal vehicle-dispatch algorithm," Omega, Elsevier, vol. 4(6), pages 711-718.
    • Handle: RePEc:eee:jomega:v:4:y:1976:i:6:p:711-718
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    Cited by:

    1. Allahyari, Somayeh & Salari, Majid & Vigo, Daniele, 2015. "A hybrid metaheuristic algorithm for the multi-depot covering tour vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 242(3), pages 756-768.
    2. B Yu & Z-Z Yang & J-X Xie, 2011. "A parallel improved ant colony optimization for multi-depot vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 183-188, January.
    3. Chen, Lijian & Chiang, Wen-Chyuan & Russell, Robert & Chen, Jun & Sun, Dengfeng, 2018. "The probabilistic vehicle routing problem with service guarantees," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 149-164.
    4. Nagy, Gabor & Salhi, Said, 2005. "Heuristic algorithms for single and multiple depot vehicle routing problems with pickups and deliveries," European Journal of Operational Research, Elsevier, vol. 162(1), pages 126-141, April.
    5. G W Kinney & R R Hill & J T Moore, 2005. "Devising a quick-running heuristic for an unmanned aerial vehicle (UAV) routing system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(7), pages 776-786, July.
    6. Matsatsinis, Nikolaos F., 2004. "Towards a decision support system for the ready concrete distribution system: A case of a Greek company," European Journal of Operational Research, Elsevier, vol. 152(2), pages 487-499, January.
    7. Rahma Lahyani & Leandro C. Coelho & Jacques Renaud, 2018. "Alternative formulations and improved bounds for the multi-depot fleet size and mix vehicle routing problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 125-157, January.
    8. Mina, Hokey & Jayaraman, Vaidyanathan & Srivastava, Rajesh, 1998. "Combined location-routing problems: A synthesis and future research directions," European Journal of Operational Research, Elsevier, vol. 108(1), pages 1-15, July.
    9. Crevier, Benoit & Cordeau, Jean-Francois & Laporte, Gilbert, 2007. "The multi-depot vehicle routing problem with inter-depot routes," European Journal of Operational Research, Elsevier, vol. 176(2), pages 756-773, January.
    10. Emre Tokgöz & Samir Alwazzi & Theodore Trafalis, 2015. "A heuristic algorithm to solve the single-facility location routing problem on Riemannian surfaces," Computational Management Science, Springer, vol. 12(3), pages 397-415, July.
    11. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    12. Tu, Wei & Fang, Zhixiang & Li, Qingquan & Shaw, Shih-Lung & Chen, BiYu, 2014. "A bi-level Voronoi diagram-based metaheuristic for a large-scale multi-depot vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 84-97.
    13. T R P Ramos & R C Oliveira, 2011. "Delimitation of service areas in reverse logistics networks with multiple depots," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1198-1210, July.
    14. Jan Christiaens & Greet Vanden Berghe, 2020. "Slack Induction by String Removals for Vehicle Routing Problems," Transportation Science, INFORMS, vol. 54(2), pages 417-433, March.
    15. Baozhen Yao & Bin Yu & Ping Hu & Junjie Gao & Mingheng Zhang, 2016. "An improved particle swarm optimization for carton heterogeneous vehicle routing problem with a collection depot," Annals of Operations Research, Springer, vol. 242(2), pages 303-320, July.
    16. Prasertsri, Peerapon & Kilmer, Richard L., 2003. "Improving Vertical Coordination From Farm-To-Plant Using A Cooperative," 2003 Annual meeting, July 27-30, Montreal, Canada 22181, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    17. Rihab Said & Maha Elarbi & Slim Bechikh & Lamjed Ben Said, 2022. "Solving combinatorial bi-level optimization problems using multiple populations and migration schemes," Operational Research, Springer, vol. 22(3), pages 1697-1735, July.
    18. Baozhen Yao & Chao Chen & Xiaolin Song & Xiaoli Yang, 2019. "Fresh seafood delivery routing problem using an improved ant colony optimization," Annals of Operations Research, Springer, vol. 273(1), pages 163-186, February.

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