Abstract To improve the train line plan quality and meet more transportation requirements, a model is presented to solve the train stops setting problem. We analyze the factors on the train setting problem and define the passenger transport efficiency. Then, an optimization model to improve the transport efficiency is constructed. The quantum particle swarm optimization algorithm is hired to solve the problem. Computing case based on Shanghai–Hangzhou high-speed railway proved the rationality of the model and the high performance of the algorithm. It is a new approach to design train stop plans which also offers constructive support for the managers of the railway bureau.
Train Stops Setting Based on a Quantum-Inspired Particle Swarm Algorithm
1st ed. 2016
01.01.2016
8 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Train Stops Setting Based on a Quantum-Inspired Particle Swarm Algorithm
British Library Conference Proceedings | 2016
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