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A Hybrid Natural Computing Approach for the VRP Problem Based on PSO, GA and Quantum Computation

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Computer Science and its Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 203))

Abstract

In this paper, a novel hybrid natural computing approach, called PGQ, combining Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and quantum computation, is introduced to solve the Vehicle Routing Problem (VRP). We propose a quantum approach, called QUP, to update the particles in PSO. And, we add GA operators to improve population quality. The simulation results show that the PGQ algorithm is very effective, and is better than simple PSO and GA, as well as PSO and GA mixed algorithm.

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References

  1. Yu, B., Yang, Z.Z., Yao, B.: An improved ant colony optimization for vehicle routing problem. Eur. J. Oper. Res. 196, 171–176 (2009)

    Article  MATH  Google Scholar 

  2. Humberto, C.B.O., Germano, C.V.: A hybrid search method for the vehicle routing problem with time windows. Ann. Oper. Res. 180, 125–144 (2010)

    Article  MATH  Google Scholar 

  3. Gong, Y.J., Zhang, J., Liu, O., Huang, R.Z., Chung, H.S.H, Shi, Y.S.: Optimizing the vehicle routing problem with time windows: a discrete particle swarm optimization approach. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 42, 254–267 (2012)

    Google Scholar 

  4. Yucenur, G.N., Nihan, C.D.: A new geometric shap-based genetic clustering algorithm for the multi-depot vehicle routing problem. Expert Syst. Appl. 38, 11859–11865 (2011)

    Article  Google Scholar 

  5. Lau, H.C.W., Chan, T.M., Tsui, W.T., Pang, W.K.: Application of genetic algorithms to solve the multidepot vehicle routing problem. IEEE Trans. Autom. Sci. Eng. 7, 383–392 (2010)

    Article  Google Scholar 

  6. Christos, D.T., Stavropoulou, F., Panagiotis, P.R.: A template-based Tabu Search algorithm for the consistent vehicle routing problem. Expert Syst. Appl. 39, 4233–4239 (2012)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Huizhou University, Huizhou, 516007, People’s Republic of China

    Kehan Zeng, Gang Peng, Zhaoquan Cai, Zhen Huang & Xiong Yang

Authors
  1. Kehan Zeng
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  2. Gang Peng
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  3. Zhaoquan Cai
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  4. Zhen Huang
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  5. Xiong Yang
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Corresponding author

Correspondence to Kehan Zeng .

Editor information

Editors and Affiliations

  1. , Electrical Engineering & ComputerScience, Mokwon University, Daejeon, Korea, Republic of (South Korea)

    Sang-Soo Yeo

  2. , Department of Computer Science, Georgia State University, Atlanta, 30302-3994, USA

    Yi Pan

  3. , Division of Computer Engineering, Mokwon University, Mokwon Gil-21, Doan-dong, Seo-gu, Daejeon, 302-729, Korea, Republic of (South Korea)

    Yang Sun Lee

  4. , Division of Business Administration, Sangmyung University, Seoul, Korea, Republic of (South Korea)

    Hang Bae Chang

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© 2012 Springer Science+Business Media Dordrecht

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Zeng, K., Peng, G., Cai, Z., Huang, Z., Yang, X. (2012). A Hybrid Natural Computing Approach for the VRP Problem Based on PSO, GA and Quantum Computation. In: Yeo, SS., Pan, Y., Lee, Y., Chang, H. (eds) Computer Science and its Applications. Lecture Notes in Electrical Engineering, vol 203. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5699-1_3

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  • DOI: https://doi.org/10.1007/978-94-007-5699-1_3

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-5698-4

  • Online ISBN: 978-94-007-5699-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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