CAJ | 학술논문

列车运行调整是铁路调度部门的重点研究对象，而自动调整是衡量铁路调度指挥自动化水平的核心。因此，以偏离运行图最小为优化目标，考虑了区间运行时分、追踪间隔时间、车站停车时分、越行约束等6个约束条件，建立了列车运行调整模型；在算法方面，针对遗传算法的缺陷，如收敛速度较慢，易于早熟收敛，提出了1种效果较好的免疫遗传算法，并对编码方案、适应度函数、抗体浓度、变异算子等进行设计改进。仿真结果表明该算法与遗传算法相比，在收敛速度，最优值以及试验成功率方面都具有更为优越的特性，可为调度人员提供1个较好的调整方案。
열차운행조정시철로조도부문적중점연구대상，이자동조정시형량철로조도지휘자동화수평적핵심。인차，이편리운행도최소위우화목표，고필료구간운행시분、추종간격시간、차참정차시분、월행약속등6개약속조건，건립료열차운행조정모형；재산법방면，침대유전산법적결함，여수렴속도교만，역우조숙수렴，제출료1충효과교호적면역유전산법，병대편마방안、괄응도함수、항체농도、변이산자등진행설계개진。방진결과표명해산법여유전산법상비，재수렴속도，최우치이급시험성공솔방면도구유경위우월적특성，가위조도인원제공1개교호적조정방안。
The adjustments to train operation is the key research topic for benefiting the railway dispatching profes-sionals ,and the automatic adjustments has become the "core measure"of the level of automation of the railway dispatc-hing .In this paper ,a train operation adjustment model is developed with the target of minimizing the deviation from train travelling diagram ,and 6 constraint conditions are taken into account ,including train running in a section ,tracing time of trains in a section ,station stop time ,train departure time ,track number ,and overtaking time .An immune genetic algo-rithm is used in this paper to solve the above model ,which is known to be free from the defects of traditional genetic algo-rithms including slow convergent speed and premature convergence .Efforts are also made to improve the algorithm by re-designing its encoding scheme ,fitness function ,antibody concentration and mutation operator .Simulation results show that ,when compared with the traditional GA ,the proposed algorithm shows more superior characteristics in convergence speed ,optimal values ,and success rates and therefore it can be used to provide better adjustment schemes for train dis-patching personnel .