Abstract: 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 .