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Particle Swarm Optimizations for Multi-type Vehicle Routing Problem with Time Windows

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Intelligent Computing Methodologies (ICIC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8589))

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Abstract

This paper presents a variant of vehicle routing problem with time windows (VRPTW) named multi-type vehicle routing problem with time windows (MT-VRPTW), which considers both multiple types of the vehicle and the uncertain number of vehicles of various types. As a consequence, the different combinations of multi-type vehicle will lead to diverse results, which should be evaluated by its own fitness function. In order to solve the proposed MT-VRPTW problem, six variants of particle swarm optimization (PSO) are used. The 2N dimensions encoding method is adopted to express the particle (N represents the number of demand point). In the simulation studies, the performances of the six PSO variants are compared and the obtained results are analyzed.

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References

  1. Solomon, M.M.: Algorithms for The Vehicle Routing And Scheduling Problems With Time Window Constraints. Operations Research 35(2), 254–265 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  2. Desrochers, M., Desrosiers, J., Solomon, M.: A New Optimization Algorithm for The Vehicle Routing Problem With Time Windows. Operations Research 40(2), 342–354 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  3. Prins, C.: A Simple And Effective Evolutionary Algorithm for The Vehicle Routing Problem. Computers & Operations Research 31(12), 1985–2002 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  4. Ombuki, B., Ross, B., Hanshar, F.: Multi-Objective Genetic Algorithms for Vehicle Routing Problem With Time Windows. Applied Intelligence 24(1), 17–30 (2006)

    Article  Google Scholar 

  5. Chen, A.L., Yang, G.K., Wu, Z.M.: Hybrid Discrete Particle Swarm Optimization Algorithm for Capacitated Vehicle Routing Problem. Journal of Zhejiang University Science A 7(4), 607–614 (2006)

    Article  MATH  Google Scholar 

  6. Belmecheri, F., Prins, C., Yalaoui, F., Amodeo, L.: Particle Swarm Optimization Algorithm for A Vehicle Routing Problem With Heterogeneous Fleet, Mixed Backhauls, And Time Windows. Journal of Intelligent Manufacturing 24(4), 775–789 (2013)

    Article  Google Scholar 

  7. Shi, Y., Eberhart, R.: A Modified Particle Swarm Optimizer. In: Proceedings of Congress on Evolutionary Computation, pp. 73–79 (1998)

    Google Scholar 

  8. Parsopoulos, K., Vrahatis, M.: UPSO: A Unified Particle Swarm Optimization Scheme. Lecture Series on Computer and Computational Sciences 1, 868–873 (2004)

    MathSciNet  Google Scholar 

  9. Mendes, R., Kennedy, J., Neves, J.: The Fully Informed Particle Swarm: Simpler, Maybe Better. IEEE Transactions on Evolutionary Computation 8(3), 204–210 (2004)

    Article  Google Scholar 

  10. Liang, J.J., Qin, A., Suganthan, P.N., Baskar, S.: Comprehensive Learning Particle Swarm Optimizer for Global Optimization of Multimodal Functions. IEEE Transactions on Evolutionary Computation 10(3), 281–295 (2006)

    Article  Google Scholar 

  11. Niu, B., Zhu, Y.L., He, X.X., Wu, H.: MCPSO: A Multi-Swarm Cooperative Particle Swarm Optimizer. Applied Mathematics and Computation 185(2), 1050–1062 (2007)

    Article  MATH  Google Scholar 

  12. Gan, X.B., Wang, Y., Li, S.H., Niu, B.: Vehicle Routing Problem With Time Windows And Simultaneous Delivery And Pick-Up Service Based On MCPSO. Mathematical Problems in Engineering, 1–11 (2012)

    Google Scholar 

  13. Kallehauge, B., Larsen, J., Madsen, O., Solomon, M.M.: Vehicle Routing Problem With Time Windows. Column Generation, 67–98 (2005)

    Google Scholar 

  14. Eberhart, R., Kennedy, J.: A New Optimizer Using Particle Swarm Theory. In: International Symposium on Micro Machine and Human Scienc, pp. 39–43 (1995)

    Google Scholar 

  15. Niu, B., Wang, H., Chai, Y.J.: Bacterial Colony Optimization. Bacterial Colony Optimization, 1–28 (2012)

    Google Scholar 

  16. Niu, B., Wang, H., Wang, J.W., Tan, L.J.: Multi-Objective Bacterial Foraging Optimization. Neurocomputing 116, 336–345 (2012)

    Article  Google Scholar 

  17. Niu, B., Wang, H., Duan, Q.Q., Li, L.: Biomimicry of Quorum Sensing Using Bacterial Lifecycle Model. BMC Bioinformatics 14, 1–13 (2013)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. College of Management, Shenzhen University, Shenzhen, 518060, China

    Xiaobin Gan, Junbiao Kuang & Ben Niu

  2. Department of Industrial and System Engineering, Hong Kong Polytechnic University, Hong Kong

    Ben Niu

  3. Hefei Institute of Intelligent Machine, Chinese Academy of Sciences, Hefei, 230031, China

    Ben Niu

Authors
  1. Xiaobin Gan
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  2. Junbiao Kuang
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  3. Ben Niu
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Electrical Engineering, University of Ulsan, 680–749, Ulsan, Korea

    Kang-Hyun Jo

  3. Department of Automation, Tsinghua University, Bejing, China

    Ling Wang

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© 2014 Springer International Publishing Switzerland

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Gan, X., Kuang, J., Niu, B. (2014). Particle Swarm Optimizations for Multi-type Vehicle Routing Problem with Time Windows. In: Huang, DS., Jo, KH., Wang, L. (eds) Intelligent Computing Methodologies. ICIC 2014. Lecture Notes in Computer Science(), vol 8589. Springer, Cham. https://doi.org/10.1007/978-3-319-09339-0_81

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  • DOI: https://doi.org/10.1007/978-3-319-09339-0_81

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09338-3

  • Online ISBN: 978-3-319-09339-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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