Solving urban electric transit network problem by integrating Pareto artificial fish swarm algorithm and genetic algorithm-Reference-Cited by-同舟云学术

Solving urban electric transit network problem by integrating Pareto artificial fish swarm algorithm and genetic algorithm

Published:2020-11-24 Issue: Volume: Page:1-28
ISSN:1547-2450
Container-title:Journal of Intelligent Transportation Systems
language:en
Short-container-title:Journal of Intelligent Transportation Systems

Author:

Liu Yi¹^ORCID,Feng Xuesong¹^ORCID,Yang Yan²,Ruan Zejing¹,Zhang Lukai¹,Li Kemeng¹

Affiliation:

1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China;

2. Guangxi Traffic Technician College, Nanning, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Applied Mathematics,Computer Science Applications,Aerospace Engineering,Automotive Engineering,Information Systems,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15472450.2020.1848561

Reference59 articles.

1. Modelling of electric and parallel-hybrid electric vehicle using Matlab/Simulink environment and planning of charging stations through a geographic information system and genetic algorithms

2. Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm

3. Transit network design with allocation of green vehicles: A genetic algorithm approach

4. A matheuristic for integrated timetabling and vehicle scheduling

5. Real-Time Bus Arrival Information System: An Empirical Evaluation

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