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International Conference on Artificial Intelligence and Computational Intelligence

AICI 2011: Artificial Intelligence and Computational Intelligence pp 163–170Cite as

Emergency Logistics Routing Optimization Algorithm Based on FSACO

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7002))

Abstract

Emergency logistics routing problem, which is premise withthe time requirements for emergency logistics and aims at maximum saving delivery time for relief supplies, is a reasonable arrangement of vehicles to run routes. According to the characteristics of time which emergency logistics emphasis on, the delivery route optimization model which the number of delivery vehicles less than demand areas is been established, besides, it has been solved by the Fish-Swarm Ant Colony Optimization (FSACO). Simulation results show that the algorithm compared with ant colony algorithm has better optimization quality.

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References

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Author information

Authors and Affiliations

  1. Information Engineering College, Tianjin University of Commerce, Tianjin, China

    Li-Yi Zhang, Teng Fei, Ting Liu & Yi Li

  2. Office of Equipment, First Hospital of Shanxi University of Medicine, Taiyuan, China

    Jin Zhang

Authors
  1. Li-Yi Zhang
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  2. Teng Fei
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  3. Ting Liu
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  4. Jin Zhang
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  5. Yi Li
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, VIC, Australia

    Hepu Deng

  2. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

  3. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  4. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Cite this paper

Zhang, LY., Fei, T., Liu, T., Zhang, J., Li, Y. (2011). Emergency Logistics Routing Optimization Algorithm Based on FSACO. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7002. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23881-9_21

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  • DOI: https://doi.org/10.1007/978-3-642-23881-9_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23880-2

  • Online ISBN: 978-3-642-23881-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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