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Multi-objective Optimization Genetic Algorithm for Multimodal Transportation

  • Conference paper
  • First Online:
Intelligent Computing and Internet of Things (ICSEE 2018, IMIOT 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 924))

Abstract

The multimodal transportation is an effective manner in reducing the transportation time and cost. However, the programming of multimodal transportation is very complex and belongs to NP difficulty problems. Therefore, an optimal model based on the graph structure was firstly formulated for the multimodal transportation with two optimal objectives including the transportation time and the transportation cost. An optimized algorithm with two layers was then proposed after characterizing the formulated model. The upper level was applied to find the global optimal Pareto fronts and the transportation path, whereas the lower level was to find the optimal path and the transportation manner. At last, a numerical simulation was performed to validate the model and the proposed algorithm. The results show that the proposed algorithm can find a series of Pareto front solutions, which indicates that the formulated model and proposed algorithm are effective and feasible.

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Author information

Authors and Affiliations

  1. School of International Business, Sichuan International Studies University, Chongqing, 400031, China

    Xiong Guiwu

  2. College of Mechanical Engineering, Chongqing University, Chongqing, 400044, China

    Xiong Guiwu & Xiaomin Dong

Authors
  1. Xiong Guiwu
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  2. Xiaomin Dong
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Corresponding author

Correspondence to Xiong Guiwu .

Editor information

Editors and Affiliations

  1. The University of Leeds, Leeds, UK

    Kang Li

  2. Shanghai University, Shanghai, China

    Minrui Fei

  3. Shanghai University, Shanghai, China

    Dajun Du

  4. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Zhile Yang

  5. Northeastern University, Shenyang, China

    Dongsheng Yang

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© 2018 Springer Nature Singapore Pte Ltd.

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Guiwu, X., Dong, X. (2018). Multi-objective Optimization Genetic Algorithm for Multimodal Transportation. In: Li, K., Fei, M., Du, D., Yang, Z., Yang, D. (eds) Intelligent Computing and Internet of Things. ICSEE IMIOT 2018 2018. Communications in Computer and Information Science, vol 924. Springer, Singapore. https://doi.org/10.1007/978-981-13-2384-3_8

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  • DOI: https://doi.org/10.1007/978-981-13-2384-3_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2383-6

  • Online ISBN: 978-981-13-2384-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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