Multi-objective train operation optimization based on particle swarm algorithm

作者：Yu Jin; He Zhengyou^*; Qian Qingquan

来源：Journal of Southwest Jiaotong University, 2010, 45(1): 70-75.

DOI：10.3969/j.issn.0258-2724.2010.01.012

• Control strategies
• Energy cost
• Multi objective
• Multi objective particle swarm optimization
• Multiobjective models
• Multiple objectives
• Particle swarm
• Particle swarm algorithm
• Performance indices
• Running time
• Simulation result
• Train control
• Train operations

To reveal the essence of multiple objectives of train operation, a multi-objective model for train operation was established and solved by using the multi-objective optimization method. Improvement and keeping diversity strategies were introduced to overcome the deficiencies of the existing MOPSO (multi-objective particle swarm optimization) algorithms. Simulation results show that the improved MOPSO algorithm can generate more than one train control strategy during a time running simultaneously, display changes in performance indices with the control strategies and decrease the shifting number of control serials sharply. Furthermore, fine tradeoff among energy cost, running time and stopping at adequate point can be obtained, as a result, the strategy suited to the train running can be selected to get an anticipated result.

• 出版日期2010
• 单位西南交通大学