Solving Multi-Robot Picking Problem in Warehouses: a Simulation Approach

Abstract

This paper focuses on the order batching problem, aiming at this order batching problem of an e-commerce unmanned warehouse multi-robot picking system, considering the complexity and uncertainty of the system. In this paper establishes a two-stage model with the objective function of maximizing the sum of the average similarity of each picking station and balancing the picking station picking times, and uses a dynamic clustering algorithm to solve the model. The simulation results show that a two-stage order batching model that considers the order similarity and the picking time balance can be established, which can reduce the number of shelves effectively and improve the picking efficiency of warehouse multi-robot system.