Abstract Accurate and prompt identification of power line outages plays an important role in the reliability and robustness of smart power grids. Line outage identification problem has been traditionally formulated as a combinatorial optimization problem and requires an exhaustive search to find an optimal solution. However, this suffers from huge computational complexity as the size of the search space grows exponentially with the number of line outages. This work proposes a computationally efficient optimization technique based on Quantum Inspired Evolutionary Algorithm (QIEA) for the identification of multiple power line outages in smart power grids. In addition to the classical QIEA, a customized version of QIEA is also proposed and its effectiveness is validated against various IEEE bus systems with multiple line outages scenarios. The simulation results demonstrate the validity and accuracy of the proposed solution.