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## An adaptive genetic algorithm for solving the optimization model of car flow organizat

 1 School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China 2 School of Railway Tracks and Transportation, Wuyi University, Jiangmen 529020, China

* Corresponding author: Wenxian Wang

Received  March 2019 Revised  May 2019 Published  December 2019

Citation: Ji Zhang, Hongxia Lv, Boer Deng, Wenxian Wang. An adaptive genetic algorithm for solving the optimization model of car flow organizat. Discrete & Continuous Dynamical Systems - S, doi: 10.3934/dcdss.2020200
##### References:

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##### References:
Topological schematic diagram of the railway line
Schematic diagram of the car flow organization code in the chromosome
Car flow organization coding mode diagram
Schematic diagram of an unreasonable traffic organization code
Schematic diagram of the traditional single point crossover of the car flow organization
Schematic diagram of traditional single point variation of car flow organization
Schematic diagram of the genetic algorithm process
Schematic diagram of simplified road network structure and car flow
Genetic algorithm convergence curve
Railway network structure related to Huang-Dao Station
Genetic algorithm convergence curve
Technical parameters of car flow and car flow organization 1
 Car flow rate $\overline{m}_{st}$ $\omega_{ff}$ $\omega_{zf}$ $\omega_{zz}$ $N_{7}$ 22 30 10 15 18 $N_{8}$ 30 40 10 15 18 $N_{9}$ 16 40 10 15 18 $N_{10}$ 50 40 10 15 18 $N_{11}$ 32 40 10 15 18
 Car flow rate $\overline{m}_{st}$ $\omega_{ff}$ $\omega_{zf}$ $\omega_{zz}$ $N_{7}$ 22 30 10 15 18 $N_{8}$ 30 40 10 15 18 $N_{9}$ 16 40 10 15 18 $N_{10}$ 50 40 10 15 18 $N_{11}$ 32 40 10 15 18
Technical parameters of main marshalling station of railroad network
 Marshalling station 1 2 3 4 5 6 $t_{k}(Hour)$ 5 5 6 5 5 6 $\overline{m}_{sk}$(Car) - 30 30 30 30 30
 Marshalling station 1 2 3 4 5 6 $t_{k}(Hour)$ 5 5 6 5 5 6 $\overline{m}_{sk}$(Car) - 30 30 30 30 30
Technical parameters of car flow and car flow organization of Huang-Dao Station
 Car flow rate $\overline{m}_{st}$ $\omega_{ff}$ $\omega_{zf}$ $\omega_{zz}$ $N_{11}$ 6 40 12 15 17 $N_{12}$ 26 50 12 15 17 $N_{13}$ 75 50 12 15 17 $N_{14}$ 18 50 12 15 17 $N_{15}$ 16 50 12 15 17 $N_{16}$ 19 50 12 15 17 $N_{17}$ 37 50 12 15 17 $N_{18}$ 70 50 12 15 17 $N_{19}$ 90 50 12 15 17
 Car flow rate $\overline{m}_{st}$ $\omega_{ff}$ $\omega_{zf}$ $\omega_{zz}$ $N_{11}$ 6 40 12 15 17 $N_{12}$ 26 50 12 15 17 $N_{13}$ 75 50 12 15 17 $N_{14}$ 18 50 12 15 17 $N_{15}$ 16 50 12 15 17 $N_{16}$ 19 50 12 15 17 $N_{17}$ 37 50 12 15 17 $N_{18}$ 70 50 12 15 17 $N_{19}$ 90 50 12 15 17
Technical parameters of main marshalling station of railroad network
 Marshalling station 1 2 3 4 5 6 $t_{k}(Hour)$ 3 3 4 3 3 4 $\overline{m}_{sk}$(Car) 40 40 40 40 40 40
 Marshalling station 1 2 3 4 5 6 $t_{k}(Hour)$ 3 3 4 3 3 4 $\overline{m}_{sk}$(Car) 40 40 40 40 40 40
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