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International Conference on Algorithms and Architectures for Parallel Processing

ICA3PP 2020: Algorithms and Architectures for Parallel Processing pp 591–605Cite as

Parallel Processing Algorithms for the Vehicle Routing Problem and Its Variants: A Literature Review with a Look into the Future

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12452))

Abstract

Vehicle Routing Problems (VRPs) are well-know combinatorial optimization problems used to design an optimal route for a fleet of vehicles to service a set of customers under a number of constraints. Due to their NP-hard complexity, a number of purely computational techniques have been proposed in recent years in order to solve them. Among these techniques, nature-inspired algorithms have proven their effectiveness in terms of accuracy and convergence speed. Some of these methods are also designed in such a way to decompose the basic problem into a number of sub-problems which are subsequently solved in parallel computing environments. It is therefore the purpose of this paper to review the fresh corpus of the literature dealing with the main approaches proposed over the past few years to solve combinatorial optimization problems in general and, in particular, the VRP and its different variants. Bibliometric and review studies are conducted with a special attention paid to metaheuristic strategies involving procedures with parallel architectures. The obtained results show an expansion of the use of parallel algorithms for solving various VRPs. Nevertheless, the regression in the number of citations in this framework proves that the interest of the research community has declined somewhat in recent years. This decline may be explained by the lack of rigorous mathematical results and practical interfaces under famous calculation softwares.

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References

  1. Abdelhafez, A., Luque, G., Alba, E.: Parallel execution combinatorics with metaheuristics: comparative study. Swarm Evol. Comput. 55, 100692 (2020)

    Article  Google Scholar 

  2. Aydin, M.E., Yigit, V.: Parallel simulated annealing Chapter 12, pp. 267–287. Wiley, Hoboken (2005)

    Google Scholar 

  3. Azzoug, Y., Boukra, A.: Bio-inspired VANET routing optimization: an overview. Artif. Intell. Rev., 1–58 (2020). https://doi.org/10.1007/s10462-020-09868-9

  4. Bach, L., Hasle, G., Schulz, C.: Adaptive large neighborhood search on the graphics processing unit. Eur. J. Oper. Res. 275(1), 53–66 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  5. Blocho, M.: Parallel algorithms for solving rich vehicle routing problems. In: Smart Delivery Systems, pp. 185–201 (2020)

    Google Scholar 

  6. Codognet, P., Munera, D., Diaz, D., Abreu, S.: Parallel Local Search. In: Hamadi, Y., Sais, L. (eds.) Handbook of Parallel Constraint Reasoning, pp. 381–417. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-63516-3_10

    Chapter  Google Scholar 

  7. Cordeau, J.F., Maischberger, M.: A parallel iterated tabu search heuristic for vehicle routing problems. Comput. Oper. Res. 39(9), 2033–2050 (2012)

    Article  Google Scholar 

  8. Crainic, T.G., Toulouse, M., Gendreau, M.: Towards a taxonomy of parallel tabu search algorithms. INFORMS J. Comput. 9(1), 61–72 (1997)

    Article  MATH  Google Scholar 

  9. Crainic, T.G., Toulouse, M.: Parallel strategies for meta-heuristics. In: Glover, F., Kochenberger, G.A. (eds.) Handbook of Metaheuristics. ISOR, vol. 57, pp. 475–513. Springer, Boston (2003). https://doi.org/10.1007/0-306-48056-5_17

    Chapter  Google Scholar 

  10. Crainic, T.G.: Parallel solution methods for vehicle routing problems. In: Golden, B., Raghavan, S., Wasil, E. (eds.) The Vehicle Routing Problem: Latest Advances and New Challenges. ORCS, vol. 43, pp. 171–198. Springer, Boston (2008). https://doi.org/10.1007/978-0-387-77778-8_8

    Chapter  Google Scholar 

  11. Crainic, T.: Parallel metaheuristics and cooperative search. In: Gendreau, M., Potvin, J.-Y. (eds.) Handbook of Metaheuristics. ISORMS, vol. 272, pp. 419–451. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-91086-4_13

    Chapter  Google Scholar 

  12. Dantzig, G.B., Fulkerson, R., Johnson, S.M.: Solution of a large-scale traveling salesman problem. Oper. Res. 2(4), 393–410 (1954)

    MathSciNet  MATH  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  14. Dokeroglu, T., Sevinc, E., Kucukyilmaz, T., Cosar, A.: A survey on new generation metaheuristic algorithms. Comput. Ind. Eng. 137, 106040 (2019)

    Article  Google Scholar 

  15. Dokeroglu, T., Pehlivan, S., Avenoglu, B.: Robust parallel hybrid artificial bee colony algorithms for the multi-dimensional numerical optimization. J. Supercomput. 76(9), 7026–7046 (2020). https://doi.org/10.1007/s11227-019-03127-7

    Article  Google Scholar 

  16. Eskandarpour, M., Ouelhadj, D., Fletcher, G.: Decision making using metaheuristic optimization methods in sustainable transportation. In: Sustainable Transportation & Smart Logistics, pp. 285–304 (2019)

    Google Scholar 

  17. Essaid, M., Idoumghar, L., Lepagnot, J., Brévilliers, M.: GPU parallelization strategies for metaheuristics: a survey. Int. J. Parallel Emergent Distrib. Syst. 34(5), 497–522 (2019)

    Article  Google Scholar 

  18. Fanlei, Y.: Autonomous vehicle routing problem solution based on artificial potential field with parallel ant colony optimization (ACO) algorithm. Pattern Recogn. Lett. 116, 195–199 (2018)

    Article  Google Scholar 

  19. Grid, M.: Bee life Parallèle sur GPU pour résoudre le problème dynamique de tournées de véhicules avec une contrainte de capacité. Université Mohamed Khider Biskra, Algérie, Thèse de Docorat (2018)

    Google Scholar 

  20. Jialong, S., Qingfu, Z.: A new cooperative framework for parallel trajectory-based metaheuristics. Appl. Soft Comput. 65, 374–386 (2018)

    Article  Google Scholar 

  21. Jagiello, S., Zelazny, D.: Solving multi-criteria vehicle routing problem by parallel tabu search on GPU. Procedia Comput. Sci. 18, 2529–2532 (2013)

    Article  Google Scholar 

  22. Kalatzantonakis, P., Sifaleras, A., Samaras, N.: Cooperative versus non-cooperative parallel variable neighborhood search strategies: a case study on the capacitated vehicle routing problem. J. Global Optim. (9), 1–22 (2019). https://doi.org/10.1007/s10898-019-00866-y

  23. Liu, F., Gui, M., Yi, C., Lan, Y.: A fast decomposition and reconstruction framework for the pickup and delivery problem with time windows and LIFO loading. IEEE Access 7, 71813–71826 (2019)

    Article  Google Scholar 

  24. Lootsma, F.A., Ragsdell, K.M.: State-of-the-art in parallel nonlinear optimization. Parallel Comput. 6, 133–155 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  25. Lopes Silva, M.A., De Souza, S.R., Freitas Souza, M.J., De Franca Filho, M.F.: Hybrid metaheuristics and multi-agent systems for solving optimization problems: a review of frameworks and a comparative analysis. Appl. Soft Comput. 71, 433–459 (2018)

    Article  Google Scholar 

  26. Marinakis, Y., Marinaki, M., Migdalas, A.: A multi-adaptive particle swarm optimization for the vehicle routing problem with time windows. Inf. Sci. 481, 311–329 (2019)

    Article  Google Scholar 

  27. Nebro, A.J., Luna, F., Talbi, E.G., Alba, E.: Parallel multiobjective optimization Chapter 16, pp. 371–394. Wiley, Hoboken (2005)

    Google Scholar 

  28. Nwana, V., Mitra, V.: Parallel mixed integer programming: a status review. Technical report, Department of Mathematical Sciences, Brunel University (2000)

    Google Scholar 

  29. Pedemonte, M., Nesmachnow, S., Cancela, H.: A survey on parallel ant colony optimization. Appl. Soft Comput. 11, 5181–5197 (2011)

    Article  Google Scholar 

  30. Prez, J.A.M., Hansen, P., Mladenovi, N.: Parallel variable neighborhood search Chapter 11, pp. 247–266. Wiley, Hoboken (2005)

    Google Scholar 

  31. Rabbouch, B., Mraihi, R., Saâdaoui, F.: A recent brief survey for the multi depot heterogenous vehicle routing problem with time windows. In: Abraham, A., Muhuri, P.K., Muda, A.K., Gandhi, N. (eds.) HIS 2017. AISC, vol. 734, pp. 147–157. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-76351-4_15

    Chapter  Google Scholar 

  32. Rabbouch, B., Saâdaoui, F., Mraihi, R.: Empirical-type simulated annealing for solving the capacitated vehicle routing problem. J. Exp. Theor. Artif. Intell. 32(3), 437–452 (2020)

    Article  Google Scholar 

  33. Rabbouch, B., Saâdaoui, F., Mraihi, R.: Efficient implementation of the genetic algorithm to solve rich vehicle routing problems. Oper. Res.: Int. J. https://doi.org/10.1007/s12351-019-00521-0

  34. Rabbouch, B., Saâdaoui, F., Mraihi, R.: Constraint programming based algorithm for solving large-scale vehicle routing problems. In: Pérez García, H., Sánchez González, L., Castejón Limas, M., Quintián Pardo, H., Corchado Rodríguez, E. (eds.) HAIS 2019. LNCS (LNAI), vol. 11734, pp. 526–539. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-29859-3_45

    Chapter  Google Scholar 

  35. Rios, E., Ochi, L.S., Boeres, C., Coelho, V.N., Coelho, I.M., Farias, R.: Exploring parallel multi-GPU local search strategies in a metaheuristic framework. J. Parallel Distrib. Comput. 111, 39–55 (2018)

    Article  Google Scholar 

  36. Shi, J., Zhang, Q.: A new cooperative framework for parallel trajectory-based metaheuristics. Appl. Soft Comput. 65, 374–386 (2018)

    Article  Google Scholar 

  37. Schryen, G.: Parallel computational optimization in operations research: a new integrative framework, literature review and research directions. Eur. J. Oper. Res. 287(1), 1–18 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  38. Starzec, M., Starzec, G., Byrski, A., Turek, W., Piȩtak, K.: Desynchronization in distributed ant colony optimization in HPC environment. Future Gener. Comput. Syst. 109, 125–133 (2020)

    Article  Google Scholar 

  39. Talbi, E.G.: Metaheuristics: From Design to Implementation. Wiley, Hoboken (2009)

    Book  MATH  Google Scholar 

  40. Tan, Y., Ding, K.: A survey on GPU-based implementation of swarm intelligence algorithms. IEEE Trans. Cybern. 46, 2028–2041 (2016)

    Article  Google Scholar 

  41. Zhang, Y., Wang, S., Ji, G.: A comprehensive survey on particle swarm optimization algorithm and its applications. Math. Problems Eng. 2015, 1–38 (2015)

    MathSciNet  MATH  Google Scholar 

  42. Zhang, Z., Sun, Y., Xie, H., Teng, Y., Wang, J.: GMMA: GPU-based multiobjective memetic algorithms for vehicle routing problem with route balancing. Appl. Intell. 49(1), 63–78 (2018). https://doi.org/10.1007/s10489-018-1210-6

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. LEONI Wiring Systems, Zone Industrielle Manzel Hayet, 5033, Monastir, Tunisia

    Bochra Rabbouch

  2. Lab: LR18ES15 Algèbre, Théorie de Nombres et Analyse Non-linéaire, Faculté des Sciences, University of Monastir, 5019, Monastir, Tunisia

    Bochra Rabbouch, Hana Rabbouch & Foued Saâdaoui

  3. Department of Statistics, Faculty of Sciences, King Abdulaziz University, P.O BOX 80203, Jeddah, 21589, Saudi Arabia

    Foued Saâdaoui

Authors
  1. Bochra Rabbouch
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  2. Hana Rabbouch
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  3. Foued Saâdaoui
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Corresponding author

Correspondence to Foued Saâdaoui .

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Editors and Affiliations

  1. Columbia University, New York, NY, USA

    Meikang Qiu

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Rabbouch, B., Rabbouch, H., Saâdaoui, F. (2020). Parallel Processing Algorithms for the Vehicle Routing Problem and Its Variants: A Literature Review with a Look into the Future. In: Qiu, M. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2020. Lecture Notes in Computer Science(), vol 12452. Springer, Cham. https://doi.org/10.1007/978-3-030-60245-1_40

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