An improved genetic algorithm is presented for the water consumption of the secondary cooling zone based on the heat transfer model of the off-line bloom caster. This study is to control the existing cooling systems and the steel casting practises in order to produce steel with best possible quality. The fitness function of improved genetic algorithm is founded according to the metallurgical criteria. This algorithm coupled with heat transfer model and metallurgical criteria, added dynamic coding method and self-adapting mutation on the original genetic algorithm can increase water distribution adaptively and improve the process efficiency. The simulation results of T91 bloom show that the optimised distribution reduced by 2% of water consumption comparing to that of before optimisation. The maximum surface cooling rate and the rate of temperature rise reduced, and the equiaxed rate increases. The function is built for explaining the relationship between the casting speed and water distribution.