Abstract: For the distributed assembly flexible job-shop scheduling problem (DAFJSP), a DAFJSP mathematical model is constructed with the minimization of the maximum completion time, the integrated energy consumption of the shop production, and the machine load as the optimization objectives. In order to solve the DAFJSP model, an improving gold rushing optimization algorithm (IGROA) is proposed, which takes the improved gold rush optimizer as the global search component, and a variety of domain search operators as the local search components. Firstly, three domain search operators are designed to improve the diversity and convergence speed of the population by performing domain search on Pareto frontier individuals. Secondly, a bid race selection method combined with simulated annealing algorithm is proposed in the population selection to improve the global optimization search capability. Finally, the algorithm is validated based on Kacem and MK algorithms, which proves the superiority of the algorithm.