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Non-linear Random Change Differential Evolution for Multi-objective Resource Allocation Problem

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Advances in Smart Vehicular Technology, Transportation, Communication and Applications (VTCA 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 128))

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Abstract

The resource allocation problem (RAP) has a wide range of applications in the transportation engineering. The differential evolution algorithm proposed to solve Chebyshev’s inequality is essentially an optimization algorithm for the most optimal solution. However, the basic differential evolution algorithm tends to fall into the local optimal solution, resulting in premature convergence of the population, especially in multi-objective resource allocation of transportation engineering. To address these problems, a Non-linear Random Change Differential Evolution was proposed to solve multi-objective resource allocation problems. With tests to the benchmark functions in CEC, the results show that both the non-linear processing and the random changing after the mutation make the result closer to the optimal value. The method make it possible to solve the NP problem of multi-objective allocation in transportation engineering.

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Acknowledgment

The authors thank Prof. Jianhua Liu with the Fujian Provincial Key Lab of Big Data Mining and Applications at the Fujian University of Technology for valuable discussions on this study.

This work was supported in part by Projects of National Science Foundation of China (No. 41471333); project 2017A13025 of Science and Technology Development Center, Ministry of Education, China; project 2018Y3001 of Fujian Provincial Department of Science and Technology; projects of Fujian Provincial Department of Education (JA14209, JA15325).

Author information

Authors and Affiliations

  1. Fujian Key Lab for Automotive Electronics and Electric Drive, Fujian University of Technology, Fuzhou, 350118, Fujian, China

    Jierui Liu, Lyuchao Liao, Fumin Zou & Qiqin Cai

  2. Fujian Provincial Key Lab of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, 350118, Fujian, China

    Jengshyang Pan

  3. Fujian Provincial Big Data Research Institute of Intelligent Transportation, Fujian University of Technology, Fuzhou, 350118, Fujian, China

    Jierui Liu, Lyuchao Liao, Jengshyang Pan, Fumin Zou & Qiqin Cai

  4. Fujian Transport Information and Telecommunication Center, Fujian Communication Department, Fuzhou, 350001, Fujian, China

    Guoqian Wang

Authors
  1. Jierui Liu
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  2. Lyuchao Liao
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  3. Jengshyang Pan
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  4. Fumin Zou
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  5. Guoqian Wang
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  6. Qiqin Cai
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Corresponding author

Correspondence to Lyuchao Liao .

Editor information

Editors and Affiliations

  1. College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian, China

    Yong Zhao

  2. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Tsu-Yang Wu

  3. School of Transportation, Fujian University of Technology, Fuzhou, Fujian, China

    Tang-Hsien Chang

  4. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  5. University of Technology Sydney, Sydney, NSW, Australia

    Lakhmi C. Jain

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Liu, J., Liao, L., Pan, J., Zou, F., Wang, G., Cai, Q. (2019). Non-linear Random Change Differential Evolution for Multi-objective Resource Allocation Problem. In: Zhao, Y., Wu, TY., Chang, TH., Pan, JS., Jain, L. (eds) Advances in Smart Vehicular Technology, Transportation, Communication and Applications. VTCA 2018. Smart Innovation, Systems and Technologies, vol 128. Springer, Cham. https://doi.org/10.1007/978-3-030-04585-2_7

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