Multi-Objective Hybrid Optimization Algorithm Using a Comprehensive Learning Strategy for Automatic Train Operation

Multi-Objective Hybrid Optimization Algorithm Using a Comprehensive Learning Strategy for Automatic Train Operation

Aiming at the problem of easy-to-fall-into local convergence for automatic train operation (ATO) velocity ideal trajectory profile optimization algorithms, an improved multi-objective hybrid optimization algorithm using a comprehensive learning strategy (ICLHOA) is proposed. Firstly, an improved par...

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Bibliographic Details
Main Authors: Longda Wang, Xingcheng Wang, Kaiwei Liu, Zhao Sheng
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Energies
Subjects:
multi-objective hybrid optimization algorithm
automatic train operation
comprehensive learning strategy
particle swarm optimization
whale optimization algorithm
fusion distance
Online Access:https://www.mdpi.com/1996-1073/12/10/1882

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