For the flexible job shop rescheduling problem with machine breakdown, an improved Imperialist Competition Algorithm (ICA) was proposed. Firstly, a flexible job shop dynamic rescheduling model was established with the maximum completion time, machine energy consumption and total delay time as the objective functions, and linear weighting method was applied to three objectives. Then, the improved ICA was proposed to retain the excellent information for the next generation. A roulette selection mechanism was added after the assimilation and revolutionary steps of the general ICA, so that the excellent genes in the initial empire were able to be retained, and the updated empire quality was better and closer to the optimal solution. Finally, after the machine breakdown, the event-driven rescheduling strategy was adopted to reschedule the unprocessed job procedures after the breakdown point. Through production examples, simulation experiments were carried out on three hypothetical machine breakdown scenarios, and the proposed algorithm was compared with improved Genetic Algorithm (GA) and Genetic and Simulated Annealing Algorithm (GASA). Experimental results show that the proposed improved ICA is effective and feasible.