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Intelligent Multi-Objective Public Charging Station Location with Sustainable Objectives

Author

Listed:
  • Qi Liu

    (Business School, Sichuan University, Chengdu 610065, China)

  • Jiahao Liu

    (Business School, Sichuan University, Chengdu 610065, China)

  • Dunhu Liu

    (School of Management, Chengdu University of Information Technology, Chengdu 610225, China)

Abstract

This paper investigates a multi-objective charging station location model with the consideration of the triple bottom line principle for green and sustainable development from economic, environmental and social perspectives. An intelligent multi-objective optimization approach is developed to handle this problem by integrating an improved multi-objective particle swarm optimization (MOPSO) process and an entropy weight method-based evaluation process. The MOPSO process is utilized to obtain a set of Pareto optimal solutions, and the entropy weight method-based evaluation process is utilized to select the final solution from Pareto optimal solutions. Numerical experiments are conducted based on large-scale GPS data. Experimental results demonstrate that the proposed approach can effectively solve the problem investigated. Moreover, the comparison of single-objective and multi-objective models validates the efficiency and necessity of the proposed multi-objective model in public charging station location problems.

Suggested Citation

  • Qi Liu & Jiahao Liu & Dunhu Liu, 2018. "Intelligent Multi-Objective Public Charging Station Location with Sustainable Objectives," Sustainability, MDPI, vol. 10(10), pages 1-18, October.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3760-:d:176596
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    References listed on IDEAS

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    Cited by:

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    2. Zaneti, Letícia A.L. & Arias, Nataly Bañol & de Almeida, Madson C. & Rider, Marcos J., 2022. "Sustainable charging schedule of electric buses in a University Campus: A rolling horizon approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).

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