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A Repetitive Grouping Max-Min Ant System for Multi-Depot Vehicle Routing Problem with Time Window

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Advances in Swarm Intelligence (ICSI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13969))

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Abstract

The vehicle routing problem is a classic NP-hard problem in modern logistics industry. The aim of this paper is to propose a repetitive grouping Max-Min Ant System (MMAS) to solve multi-depot vehicle routing problem with time window. The whole algorithm adopts the framework of decomposition. Firstly, the algorithm defines boundary customers and groups them into corresponding depot groups repeatedly for sub-problem optimization. Secondly, the algorithm uses adaptive range technique to determine the size of boundary customers, so as to balance the convergence and resource consumption of the algorithm. Finally, local search operator is integrated into the sub-problem optimization to improve the search ability. The algorithm is tested on several benchmark problems. Experimental results show that the proposed algorithm can effectively improve the performance in most cases compared with several state-of-the-art evolutionary algorithms.

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References

  1. Bae, H., Moon, I.: Multi-depot vehicle routing problem with time windows considering delivery and installation vehicles. Appl. Math. Model. 40(13–14), 6536–6549 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  2. Bettinelli, A., Ceselli, A., Righini, G.: A branch-and-cut-and-price algorithm for the multi-depot heterogeneous vehicle routing problem with time windows. Transport. Res. Part C: Emerg. Technol. 19(5), 723–740 (2011)

    Article  MATH  Google Scholar 

  3. Brandão, J.: A memory-based iterated local search algorithm for the multi-depot open vehicle routing problem. Eur. J. Oper. Res. 284(2), 559–571 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  4. Cordeau, J.F., Laporte, G., Mercier, A.: A unified tabu search heuristic for vehicle routing problems with time windows. J. Oper. Res. Society 52(8), 928–936 (2001)

    Article  MATH  Google Scholar 

  5. Cordeau, J.F., Laporte, G., Mercier, A.: Improved tabu search algorithm for the handling of route duration constraints in vehicle routing problems with time windows. J. Oper. Res. Society 55(5), 542–546 (2004)

    Article  MATH  Google Scholar 

  6. Dantzig, G.B., Ramser, J.H.: The truck dispatching problem. Manage. Sci. 6(1), 80–91 (1959)

    Article  MathSciNet  MATH  Google Scholar 

  7. Desaulniers, G., Lavigne, J., Soumis, F.: Multi-depot vehicle scheduling problems with time windows and waiting costs. Eur. J. Oper. Res. 111(3), 479–494 (1998)

    Article  MATH  Google Scholar 

  8. Dorigo, M., Maniezzo, V., Colorni, A.: Ant system: optimization by a colony of cooperating agents. IEEE Trans. Syst., Man, Cybern., Part B (Cybernetics) 26(1), 29–41 (1996)

    Google Scholar 

  9. Erdoğan, G.: An open source spreadsheet solver for vehicle routing problems. Comput. Oper. Res. 84, 62–72 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  10. Fan, H., Yang, X., Li, D., Li, Y., Liu, P., Wu, J.: Half-open multi-depot vehicle routing problem based on joint distribution mode of fresh food. Comput. Integ. Manufact. Syst 25, 256–266 (2019)

    Google Scholar 

  11. Gao, J., Gu, F., Hu, P., Xie, Y., Yao, B.: Automobile chain maintenance parts delivery problem using an improved ant colony algorithm. Adv. Mech. Eng. 8(9), 1687814016665297 (2016)

    Article  Google Scholar 

  12. Kallehauge, B., Larsen, J., Madsen, O.B., Solomon, M.M.: Vehicle routing problem with time windows. In: Column generation, pp. 67–98. Springer (2005). https://doi.org/10.1007/0-387-25486-2_3

  13. Koç, Ç., Bektaş, T., Jabali, O., Laporte, G.: The fleet size and mix location-routing problem with time windows: formulations and a heuristic algorithm. Eur. J. Oper. Res. 248(1), 33–51 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  14. Li, J., Li, Y., Pardalos, P.M.: Multi-depot vehicle routing problem with time windows under shared depot resources. J. Comb. Optim. 31, 515–532 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  15. Mancini, S.: A real-life multi depot multi period vehicle routing problem with a heterogeneous fleet: formulation and adaptive large neighborhood search based matheuristic. Transp. Res. Part C: Emerg. Technol. 70, 100–112 (2016)

    Article  Google Scholar 

  16. Martins, L.d.C., Bayliss, C., Juan, A.A., Panadero, J., Marmol, M.: A savings-based heuristic for solving the omnichannel vehicle routing problem with pick-up and delivery. Transport. Res. Proc. 47, 83–90 (2020)

    Google Scholar 

  17. Nan, W., Shiqi, L., Junfeng, W.: Vehicle routing with time windows in material delivery for automobile general assembly line. Ind. Eng. J. 15(2), 94 (2012)

    Google Scholar 

  18. Niu, M., Liu, R., Wang, H.: A max-min ant system based on decomposition for the multi-depot cumulative capacitated vehicle routing problem. In: 2021 IEEE Congress on Evolutionary Computation (CEC), pp. 620–627. IEEE (2021)

    Google Scholar 

  19. Noori, S., Ghannadpour, S.F.: High-level relay hybrid metaheuristic method for multi-depot vehicle routing problem with time windows. J. Math. Modell. Algorithms 11(2), 159–179 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  20. Polacek, M., Hartl, R.F., Doerner, K., Reimann, M.: A variable neighborhood search for the multi depot vehicle routing problem with time windows. J. Heuristics 10(6), 613–627 (2004)

    Article  Google Scholar 

  21. Rahimi-Vahed, A., Crainic, T.G., Gendreau, M., Rei, W.: Fleet-sizing for multi-depot and periodic vehicle routing problems using a modular heuristic algorithm. Comput. Oper. Res. 53, 9–23 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  22. Thangiah, S.R., Osman, I.H., Sun, T.: Hybrid genetic algorithm, simulated annealing and tabu search methods for vehicle routing problems with time windows. Computer Science Department, Slippery Rock University, Technical Report SRU CpSc-TR-94-27 69 (1994)

    Google Scholar 

  23. Toth, P., Vigo, D.: The vehicle routing problem. SIAM (2002)

    Google Scholar 

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Acknowledgements

This work was supported by the Provincial Natural Science Foundation of Shaanxi of China (No. 2019JZ-26).

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Authors and Affiliations

  1. Key Lab of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi’an, 710071, China

    Wanfeng Chen, Ruochen Liu & Mengyi Niu

  2. 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang, China

    Qi Guo

Authors
  1. Wanfeng Chen
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  2. Ruochen Liu
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  3. Qi Guo
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  4. Mengyi Niu
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Corresponding author

Correspondence to Ruochen Liu .

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Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. Harbin Institute of Technology, Shenzhen, China

    Wenjian Luo

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Chen, W., Liu, R., Guo, Q., Niu, M. (2023). A Repetitive Grouping Max-Min Ant System for Multi-Depot Vehicle Routing Problem with Time Window. In: Tan, Y., Shi, Y., Luo, W. (eds) Advances in Swarm Intelligence. ICSI 2023. Lecture Notes in Computer Science, vol 13969. Springer, Cham. https://doi.org/10.1007/978-3-031-36625-3_30

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  • DOI: https://doi.org/10.1007/978-3-031-36625-3_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36624-6

  • Online ISBN: 978-3-031-36625-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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