Intelligent Multi-Objective Public Charging Station Location with Sustainable Objectives

Intelligent Multi-Objective Public Charging Station Location with Sustainable Objectives

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...

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Bibliographic Details
Main Authors: Qi Liu, Jiahao Liu, Dunhu Liu
Format: Article
Language:English
Published: MDPI AG 2018-10-01
Series:Sustainability
Subjects:
sustainability
public charging station
GPS trajectory data
vehicle trips
Online Access:http://www.mdpi.com/2071-1050/10/10/3760
Description
Summary: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.
ISSN:2071-1050

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