Firefly Algorithm Order Batching Problem Based on Local Search Optimization

Order processing efficiency determines the stability and efficiency of the whole logistics system, which is of great significance for warehouse operation management. The order batch problem(OBP) is a combinatorial optimization problem that arises in the warehouse order picking process. In this paper, we propose to use the Firefly Algorithm (FA) to solve the order batch processing problem and optimize the algorithm using local search optimization. The algorithm is utilized to verify the effectiveness and efficiency of the Firefly algorithm on the order batching problem for an instance. Also, a comparison highlights the usefulness of local search operations for optimizing the firefly algorithm. The experimental results show that the optimized FA exhibits faster convergence speed during the iteration process and is not easy to fall into the local optimum, and the final distance required by the picker is 1113 m. Compared with the unoptimized FA, the optimized algorithm significantly improves the optimization effect while maintaining a lower time overhead. Specifically, the average running time of the optimized FA is 10.8 seconds, which is a significant optimization effect with low additional time overhead. This study provides a new implementation idea for the solution of OBP problems and the application of FA.