吉林大学学报(工学版) ›› 2012, Vol. 42 ›› Issue (增刊1): 261-265.

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Dynamic empty car scheduling optimization based on immune clonal with cloud preference

JING Yun, HE Shi-wei, SONG Rui, LI Hao-dong   

  1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
  • Received:2012-04-07 Online:2012-09-01 Published:2012-09-01

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Abstract: By proposing the concept of timeline,transforms dynamic vehicle scheduling problem into a series of static vehicle scheduling problems. Considering cloud preference objective function and empty car delay time constraint,the cloud preference model of dynamic empty car scheduling was built. The non-dominated antibodies were proportionally immune clonal according to their cloud preference,which were defined by their cloud application preferences. It is beneficial to enhance the forecasting accuracy of the immune gene manipulation,and to increase the speed of finding the optimal solution based on the application preference. Experimental results show that the proposed algorithm improves the availability,load balancing deviation and valid time of the dynamic empty car scheduling system,so can meet the real-time calculation requirement.

Key words: computer application, dynamic empty car scheduling, immune clonal, cloud model, cloud preference

CLC Number: 

  • TP391
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