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OVRP_ICA: An Imperialist-Based Optimization Algorithm for the Open Vehicle Routing Problem

  • Shahab Shamshirband
  • Mohammad Shojafar
  • Ali Asghar Rahmani Hosseinabadi
  • Ajith Abraham
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9121)

Abstract

Open vehicle routing problem (OVRP) is one of the most important problems in vehicle routing, which has attracted great interest in several recent applications in industries. The purpose in solving the OVRP is to decrease the number of vehicles and to reduce travel distance and time of the vehicles. In this article, a new meta-heuristic algorithm called OVRP_ICA is presented for the above-mentioned problem. This is a kind of combinatorial optimization problem that can use a homogeneous fleet of vehicles that do not necessarily return to the initial depot to solve the problem of offering services to a set of customers exploiting the imperialist competitive algorithm. OVRP_ICA is compared with some well-known state-of-the-art algorithms and the results confirmed that it has high efficiency in solving the above-mentioned problem.

Keywords

Metaheuristic algorithms Open vehicle routing problem (OVRP) Imperialist competitive algorithm (ICA) Combinatorial optimization problem 

Notes

Acknowledgement

This work was also supported in the framework of the IT4 Innovations Centre of Excellence project, reg. no. CZ.1.05/1.1.00/02.0070 by operational programme ‘Research and Development for Innovations’ funded by the Structural Funds of the European Union and state budget of the Czech Republic, EU.

References

  1. 1.
    Li, F., Golden, B., Wasil, E.: The open vehicle routing problem: Algorithms, large-scale test problems, and computational results. COR 34, 2918–2930 (2007)zbMATHGoogle Scholar
  2. 2.
    Fleszar, K., et al.: A variable neighborhood search algorithm for the open vehicle routing problem. EJOR 195, 803–809 (2009)CrossRefzbMATHGoogle Scholar
  3. 3.
    Sariklis, D., Powell, S.: A heuristic method for the open vehicle routing problem. JORS 51, 564–573 (2000)CrossRefzbMATHGoogle Scholar
  4. 4.
    Reza, C.M.F.S., Mekhilef, S.: Online stator resistance estimation using artificial neural network for direct torque controlled induction motor drive. In: IEEE 8th ICIEA, pp. 1486–1491 (2013)Google Scholar
  5. 5.
    Cao, E., Lai, M., Yang, H.: Open vehicle routing problem with demand uncertainty and its robust strategies. ESWA 41, 3569–3575 (2014)Google Scholar
  6. 6.
    Cao, E., Lai, M., Yang, H.: The open vehicle routing problem with fuzzy demands. Exp. Sys. Apps. 37, 2405–2411 (2010)CrossRefGoogle Scholar
  7. 7.
    Yu, Sh, Ding, Ch., Zhu, K.: A hybrid GA–TS algorithm for open vehicle routing optimization of coal mines material. ESWA 38, 10568–10573 (2011)Google Scholar
  8. 8.
    Repoussisa, P.P., Tarantilis, C.D., Braysy, O., Ioannou, G.: A hybrid evolution strategy for the open vehicle routing problem. Comp. Oper. Res. 37, 443–455 (2010)CrossRefGoogle Scholar
  9. 9.
    Huang, F., Liu, C.: A hybrid tabu search for open vehicle routing problem. CCTAE 1, 132–134 (2010)Google Scholar
  10. 10.
    Huang, F. Liu, C.: An improved tabu search for open vehicle routing problem. In: Management and Service Science (MASS), pp. 1–4 (2010)Google Scholar
  11. 11.
    Shamshirband, Sh., et al.: OSGA: genetic-based open-shop scheduling with consideration of machine maintenance in small and medium enterprises. ANOR, pp. 1–16. Springer, New York (2015)Google Scholar
  12. 12.
    Shamshirband, Sh., et al.: A solution for multi-objective commodity vehicle routing problem by NSGA-II. IEEE HIS 2014, 12–17 (2014)Google Scholar
  13. 13.
    Hu, F., Wu, F.: Diploid hybrid particle swarm optimization with differential evolution for open vehicle routing problem. In: WCICA, pp. 2692–2697 (2010)Google Scholar
  14. 14.
    Schneider, H., Reinholz, A.: Integrating Variable Neighborhood Search into a Hybrid Evolutionary Strategy for the Open Vehicle Routing Problem. In: EU/MEeting 2008 pp. 1–6. Troyes, France (2008)Google Scholar
  15. 15.
    Zachariadis, E.E., Kiranoudis, ChT: An open vehicle routing problem metaheuristic for examining wide solution neighborhoods. COR 37, 712–723 (2010)zbMATHGoogle Scholar
  16. 16.
    MirHassani, S.A., Abolghasemi, N.: A particle swarm optimization algorithm for open vehicle routing problem. ESWA 38, 11547–11551 (2011)Google Scholar
  17. 17.
    Marinakis, Y., Marinaki, M.: A bumble bees mating optimization algorithm for the open vehicle routing problem. Swarm Evol. Comp. 15, 80–94 (2014)CrossRefGoogle Scholar
  18. 18.
    Rababah A.M.: Taylor theorem for planar curves. AMS 119, 803–810 (1993)CrossRefzbMATHMathSciNetGoogle Scholar
  19. 19.
    Atabani, A.E., et al.: A comprehensive review on biodiesel as an alternative energy resource and its characteristics. RSER 16(4), 2070–2093 (2012)Google Scholar
  20. 20.
    Rababah A.M.: High order approximation method for curves. Com. Aid. Geom. Des. 12, 89–102 (1995)CrossRefzbMATHMathSciNetGoogle Scholar
  21. 21.
    Atashpaz-Gargari, E., Lucas, C.: Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition. In: IEEE ICEC, pp. 4661–4667 (2007)Google Scholar
  22. 22.
    Toth, P., Vigo, D.: The Vehicle Routing Problem. Society for Industrial and Applied Mathematics, Philadelphia (2001)Google Scholar
  23. 23.
    Fisher, M.: Optimal solution of vehicle routing problems using minimum k-trees. Oper. Res. 42, 626–642 (1994)CrossRefzbMATHMathSciNetGoogle Scholar
  24. 24.

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Shahab Shamshirband
    • 1
  • Mohammad Shojafar
    • 2
  • Ali Asghar Rahmani Hosseinabadi
    • 3
  • Ajith Abraham
    • 4
    • 5
  1. 1.Department of Computer System and Technology, Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala LumpurMalaysia
  2. 2.Department of Information Engineering Electronics and Telecommunications (DIET)University Sapienza of RomeRomeItaly
  3. 3.Young Research Club, Behshahr BranchIslamic Azad UniversityTehranIran
  4. 4.Machine Intelligence Research Labs (MIR Labs)Scientific Network for Innovation, and Research ExcellenceAuburnUSA
  5. 5.IT4Innovations - Center of ExcellenceVSB - Technical University of OstravaOstravaCzech Republic

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