This study analyzed the influence factors of urban rail train operations. Then, the multi-objective optimization model was built based on the matching capacity and needs, maximum profits, and comfort levels of passengers from the view of energy conservation. An improved genetic algorithm is used to solve the model. The results are helpful in implementing fast-slow operation modes for rail transit enterprises, improving the efficiency of transit operations, reducing operating costs, and improving the levels of service. A solution is presented to balance the morning-evening peak periods and off- peak periods.
Urban Rail Train Marshalling Optimization Based on Multiple Operation Modes
14th COTA International Conference of Transportation Professionals ; 2014 ; Changsha, China
CICTP 2014 ; 1652-1660
2014-06-24
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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