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A variable neighborhood-based heuristic for the heterogeneous fleet vehicle routing problem

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  • Imran, Arif
  • Salhi, Said
  • Wassan, Niaz A.

Abstract

The heterogeneous fleet vehicle routing problem is investigated using some adaptations of the variable neighborhood search (VNS). The initial solution is obtained by Dijkstra's algorithm based on a cost network constructed by the sweep algorithm and the 2-opt. Our VNS algorithm uses several neighborhoods which are adapted for this problem. In addition, a number of local search methods together with a diversification procedure are used. Two VNS variants, which differ in the order the diversification and Dijkstra's algorithm are used, are implemented. Both variants appear to be competitive and produce new best results when tested on the data sets from the literature. We also constructed larger data sets for which benchmarking results are provided for future comparison.

Suggested Citation

  • Imran, Arif & Salhi, Said & Wassan, Niaz A., 2009. "A variable neighborhood-based heuristic for the heterogeneous fleet vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 197(2), pages 509-518, September.
    • Handle: RePEc:eee:ejores:v:197:y:2009:i:2:p:509-518
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    8. Houda Derbel & Bassem Jarboui & Rim Bhiri, 2019. "A skewed general variable neighborhood search algorithm with fixed threshold for the heterogeneous fleet vehicle routing problem," Annals of Operations Research, Springer, vol. 272(1), pages 243-272, January.
    9. He, Pengfei & Hao, Jin-Kao, 2023. "Memetic search for the minmax multiple traveling salesman problem with single and multiple depots," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1055-1070.
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    12. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "Thirty years of heterogeneous vehicle routing," European Journal of Operational Research, Elsevier, vol. 249(1), pages 1-21.
    13. 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.
    14. 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.
    15. Leung, Stephen C.H. & Zhang, Zhenzhen & Zhang, Defu & Hua, Xian & Lim, Ming K., 2013. "A meta-heuristic algorithm for heterogeneous fleet vehicle routing problems with two-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 225(2), pages 199-210.
    16. Janssens, Jochen & Van den Bergh, Joos & Sörensen, Kenneth & Cattrysse, Dirk, 2015. "Multi-objective microzone-based vehicle routing for courier companies: From tactical to operational planning," European Journal of Operational Research, Elsevier, vol. 242(1), pages 222-231.
    17. Ferreira, Kamyla Maria & de Queiroz, Thiago Alves & Munari, Pedro & Toledo, Franklina Maria Bragion, 2024. "A variable neighborhood search for the green vehicle routing problem with two-dimensional loading constraints and split delivery," European Journal of Operational Research, Elsevier, vol. 316(2), pages 597-616.
    18. Wei, Lijun & Zhang, Zhenzhen & Zhang, Defu & Lim, Andrew, 2015. "A variable neighborhood search for the capacitated vehicle routing problem with two-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 243(3), pages 798-814.
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    21. Pierre Hansen & Nenad Mladenović & José Moreno Pérez, 2010. "Variable neighbourhood search: methods and applications," Annals of Operations Research, Springer, vol. 175(1), pages 367-407, March.

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