A new scheduling model for the bulk ore blending process in iron-making industry is presented , by converting the process into an assembly flow shop scheduling problem with sequence-depended setup time and limited intermediate buffer , and it facilitates the scheduling optimization for this process.To find out the optimal solution of the scheduling problem , an improved genetic algorithm hybridized with problem knowledge-based heuristics is also proposed , which provides high-quality initial solutions and fast searching speed.The efficiency of the algorithm is verified by the computational experiments.