NDLI: Study on passenger train stopping scheme based on improved Particle Swarm Optimization algorithm

Content Provider	IEEE Xplore Digital Library
Author	Shuang Wang Peng Zhao Ke Qiao
Copyright Year	2009
Description	Author affiliation: School of Traffic and Transportation, Beijing Jiaotong University, China (Shuang Wang; Peng Zhao; Ke Qiao)
Abstract	This paper develops a multi-objective optimization model for the passenger train stopping scheme on high-speed railway lines. Minimizing the stopping times for all passenger trains, minimizing travel distance of empty trains and minimizing the number of transfer passengers are the three planning objectives of the model. For a given travel demand and specified capacity of stops, the model is solved by heuristic algorithm. An improved discrete Particle Swarm Optimization (PSO) algorithm is presented to determine the best-compromise train stopping scheme with high effectiveness and stability. In the algorithm, a stop based representation is designed, and a new method is used to update the position and velocity of particles. In order to keep the particle swarm algorithm from premature stagnation, the simulated annealing algorithm, which has local search ability, is combined with the PSO algorithm to make elaborate search near the optimal solution, then the quality of solutions is improved effectively. An empirical study on a given small railway network is conducted to demonstrate the effectiveness of the model and the performance of the algorithm. The experimental results show that the hybrid algorithm has great advantages in both success rate and convergence speed compared with other discrete PSO algorithm and genetic algorithm, and an optimal set of stopping schemes can always be generated for a given demand. To achieve the best planning outcome, the stopping schemes should be flexibly planned, and not constrained by specific ones as often set by the planner.
Starting Page	821
Ending Page	826
File Size	131920
Page Count	6
File Format	PDF
ISBN	9781424447541
DOI	10.1109/ICICISYS.2009.5358034
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-11-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Stability Heuristic algorithms Birds Passenger train stopping scheme Electronic mail Multi-objective programming Particle swarm optimization Scheduling algorithm High-speed railway lines Simulated annealing Particle swarm optimization algorithm Traffic control Simulated annealing algorithm Rail transportation
Content Type	Text
Resource Type	Article

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