This paper proposes a novel dual resource constrained (DRC) scheduling problem under identical parallel machine environment that consider operator working modes and moving activity between machines with regards to the makespan minimization objective. We define the working modes as all operator activities when the operators interact with the machines such as loading, setup, controlling, and unloading. Firstly, we provide the mathematical model of the problem using Mixed Integer Linear Programming (MILP). We add unloading activity beside setup to be included in the model. Also, we consider the moving activity that is usually neglected in DRC scheduling problem. Moreover, we propose a permutation-based genetic algorithm (PGA) to tackle the computational burden of the bigger size problem. Then, we run a full factorial experiment with replication to compare the solution quality and computational time of our PGA to the solver and random search method. The results show that our proposed PGA could solve the problem in a reasonable time that is faster than the solver with a good quality solution that is better than random search.