Initial Population Optimization Sparrow Search Algorithm for Warehouse AGV Path Planning

To address the excessive randomness in the initial population that may lead to suboptimal first-generation solutions in the storage system path planning using the Sparrow Search Algorithm (SSA), this paper propose the Initial Population Optimized Sparrow Search Algorithm (IPOSSA). IPOSSA utilizes the good point set method to distribute initial population values uniformly within the permissible range, thereby bringing the first-generation solution closer to the optimal value. Simulation results confirm the effectiveness of this approach, showing that IPOSSA shortens the average optimal path by 5.89% compared to SSA, converges more quickly, and mitigates the tendency to fall into local optima. Overall, the improved method demonstrates significant effectiveness.