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Research of Emergency Logistics Distribution Routing Optimization Based on Improved Ant Colony Algorithm

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Emerging Research in Artificial Intelligence and Computational Intelligence (AICI 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 237))

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Abstract

Emergency relief has characteristics of complexity, urgency, sustainability, technicality, and so on. In this paper a mathematical model to seek the shortest delivery time as the ultimate goal is established based on these characteristics, which is on the core of characteristics with the urgency and consider both the road conditions and on shortage of demand point of relief supplies. The problem of emergency logistics distribution routing optimization is solved by the improved ant colony algorithm—Fish-Swarm Ant Colony Optimization, simulation results show that, compared with basic ant colony algorithm, Fish-Swarm Ant Colony Optimization can find the higher quality to solve the problem of emergency logistics distribution routing optimization.

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Author information

Authors and Affiliations

  1. Suzhou Industrial Park Institute of Services Outsourcing, Suzhou, China

    Huijie Ding

Authors
  1. Huijie Ding
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Editor information

Editors and Affiliations

  1. School of Business Information technology, RMIT University, GPO Box 2476V, 3000, Melbourne, Victoria, Australia

    Hepu Deng

  2. Department of Computer Science and Technology, Tongji University, Shanghai, China

    Duoqian Miao

  3. Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan, Hong Kong, SAR, China

    Fu Lee Wang

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

    Jingsheng Lei

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© 2011 Springer-Verlag Berlin Heidelberg

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Ding, H. (2011). Research of Emergency Logistics Distribution Routing Optimization Based on Improved Ant Colony Algorithm. In: Deng, H., Miao, D., Wang, F.L., Lei, J. (eds) Emerging Research in Artificial Intelligence and Computational Intelligence. AICI 2011. Communications in Computer and Information Science, vol 237. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24282-3_60

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  • DOI: https://doi.org/10.1007/978-3-642-24282-3_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24281-6

  • Online ISBN: 978-3-642-24282-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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