The resource constrained project scheduling problem(RCPSP) requires that the starting time of each activity should be scheduled so as to achieve an optimal target under the condition of satisfying the relevant constraints. It has attracted many researchers’ attention and has been applied to many research fields. The classical RCPSP model only focuses on the minimization of project duration time and ignores the impact of other factors on the overall project, which is not suitable for real applications. Based on the classical RCPSP model, this paper introduces a multi-objective model by exploring the optimal resource equalization as the optimization objective, which can enrich the application scenario of RCPSP models. Due to the large number of control relationships between activities in the proposed new model, it takes a lot of time to evaluate the infeasible solutions by using traditional heuristic multi-objective algorithms. In order to improve the efficiency of the algorithm, this paper proposes a new algorithm known as NSGA-IIs. The NSGA-IIs algorithm divides each activity into several subsets based on the control relationship between activities and generates new individuals based on subsets in the initialization and crossover mutation stages, which can avoid the generation of infeasible solutions and improve the performance of the algorithm effectively. The set coverage measure is employed as a performance indicator, and the experimental results show that the proposed algorithm outperforms the classical RCPSP algorithms.