摘要
重载铁路集疏运调度系统车流组织优化问题涉及到空车与重车的协同优化,只有将二者结合才能够制定完整的车流组织方案.论文首先通过分析系统空重车流组织特征,以车辆周转时间最小为目标,建立基于企业需求与铁路供给的车流综合优化模型.其次以目标函数为抗体,约束条件为抗原,构建基于信息熵的亲和度表示方式,利用免疫克隆算法求解集疏运系统车流组织方案.在求解的过程中,利用免疫克隆算子实现繁殖,通过抗体浓度对种群规模进行控制,防止早熟收敛.最后仿真结果表明,与遗传算法和粒子群算法相比,本文算法的平均搜索时间减少了25%、49%.
Abstract： The heavy haul railway scheduling system of optimization model of car flow organization should combine With both the empty and loaded car flow. Through analyzing the empty and loaded ear flow organization, this paper develops a comprehensive optimization model based on the ability of station and railways. The goal is the minimum turnaround time of cars in the loading end of heavy haul railway. Then, based on the information entropy, representation of affinity degree is proposed. For antibody to the objective function and antigen constraint conditions, the immune clone algorithm is adopted for car flow organization in the loading end of loaded haul railway. In the solving process, premature convergence can be prevented using the immune cloning to achieve reproduction, and using the antibody concentration to control thepopulation size. Finally, the simulation results show that the average search time of the proposed algorithm is reduced by 25% and 49% compared with the GA and PSO.
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2012年第5期123-129,共7页
Journal of Transportation Systems Engineering and Information Technology
基金
铁道部科技研究开发计划重大课题(2011X004)
中国博士后科学基金(20110490283)
中央高校基本科研业务费专项资金(2011JBM253)
关键词
铁路运输
车流组织方案
免疫克隆算法
重载铁路
车辆周转时间
railway transportation
car flow organization plan
immune Clonal algorithm
heavy haulrailway
turnaround time
