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Jun.  2016
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HUANG Xiaobo, ZHU Ning, ZHU Jianhua, LI Geng. Routing Optimization of Multiple Rubber-tired Gantry Cranes Considering Carbon Emission[J]. Journal of Transport Information and Safety, 2016, 34(3): 101-107. doi: 10.3963/j.issn1674-4861.2016.03.014
Citation: HUANG Xiaobo, ZHU Ning, ZHU Jianhua, LI Geng. Routing Optimization of Multiple Rubber-tired Gantry Cranes Considering Carbon Emission[J]. Journal of Transport Information and Safety, 2016, 34(3): 101-107. doi: 10.3963/j.issn1674-4861.2016.03.014

Routing Optimization of Multiple Rubber-tired Gantry Cranes Considering Carbon Emission

doi: 10.3963/j.issn1674-4861.2016.03.014
  • Publish Date: 2016-06-28
  • Rubber-tired gantry cranes (RTGs)are important resources in container terminals.It is essential to schedule multiple RTGs effectively so as to reduce both carbon emissions and operating costs.Based on the feature of RTGs that they cannot cross each other,and other constrains,three sources of carbon emission during moving process, loading and unloading process,and preparing process are taken into consideration.A mathematical model of route pro-gramming for RTGs is developed to minimize the carbon emissions.For the computational complexity of a mixed integer programming model,a path strategy for RTGs is designed.A simulated annealing algorithm is applied to find the near-optimal solution.Numerical experiments are performed to evaluate the effects of new methods in three aspects:route lengths,total carbon emissions,and operational efficiency.Compared with the shortest path optimization method,this new model can increase the route lengths by 8.82%,while the runtime only increases by 0.21 s.The carbon emission re-duces by 3.3%.This method can guarantee working efficiency of RTGs,and effectively solve the problem of RTGs rou-ting with low-carbon emission.Compared with the genetic algorithm and the ant colony optimization,the accuracy of this proposed algorithm can improve the accuracy by 1.13% and 2.24%,respectively.In addition,the operational efficiency increases by 9.82% and 5.92%,respectively.

     

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