Abstract: A quantum-inspired cuckoo co-search algorithm is proposed to optimize the shortest path for garbage collection. First, the Bloch spherical coordinate quantum coding is used to enlarge the solution space. Then, a quantum cuckoo search strategy based on differential evolution is designed to realize the improvement of poor individuals and the information exchange between the inferior and dominant individuals. This strategy can enhance the global searching ability. Finally, a local neighborhood search algorithm is developed to further improve the quality of the solution. The convergence of the proposed algorithm is shown via a theoretical analysis. The simulation experiment is based on wireless sensor networks. Compared with the traditional genetic algorithm and the standard quantum-inspired cuckoo search algorithm, the proposed algorithm for the optimal solution and average solutions with the shortest path for garbage collection are improved by 20%~40%, which proves the superiority of the proposed algorithm.