Abstract： In order to reduce the complexity of multi-objective optimization in flexible jobshop scheduling and improve optimization efficiency, a multiobjective integrated optimization method with multiple resource constraints was proposed in this paper. Firstly, an integrated optimization model was established according to the objectives of minimum completion time, optimal human resource allocation plan, maximum equipment load and lowest production costs. Besides, in  view of the explosive characteristics of combination model,  an integrated scheduling rule for multiple resources allocation was presented to reduce the model complexity. As for the selection strategies of the scheduling rules, the rules with a high probability were preferentially selected through adjusting the probability of rules. In addition, the multiplerule guiding mechanism was adopted to push the search process toward the target direction. Furthermore,  the improved nondominated sorting genetic algorithm (NSGAⅡ) was adopted to obtain the Pareto solution sets of different probability values of the rules. Finally, the effectiveness of the proposed method was verified by simulation comparison.