Abstract：Research purposes ： At present， China has entered a period with a growing number of urban rail transit network operation phases，which puts ona higher demand the emergency rescue system of urban rail transit network, in whichthe rescue station emergency is key to the rescue system. Therefore， we propose a multi - step approach with rolling solving particle dimension to build adaptive model for solving urban rail transit network multi - objective emergency rescue station location problem，and we also use Matlab with a combination of digital map，to cover the whole of Beijing subway with calculated net minimum number of emergency rescue station and the best location distribution.
Research conclusions ： ( 1 ) This paper presents improved method for solving multi - step rolling particle swarm optimization clustering algorithm，the improved algorithm can adaptively determine cluster number. (2) The application of the improved particle swarm optimization algorithm， automatic solving different rail transit network in emergency rescue station for a minimum number is better than the existing related research. (3 ) Adaptive particle swarm optimizationproposed in this paper，can also be used to solve the same condition clustering，clustering boundaries clear of similar problems. (4) The impact of this article additional weights in the fitness function solve the selection process of the multi - objective constraint problem.
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2015, Vol. 32 
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