Layout Design for Intelligent Warehouse by Evolution with Fitness Approximation
This work addresses the costly and suboptimal manual layout design process in the express industry, offering an automated solution for warehouse efficiency.
The paper tackles the problem of automating warehouse layout design for intelligent warehouses using autonomous robots, proposing a two-layer evolutionary algorithm with fitness approximation to improve transportation efficiency, and shows that the method outperforms heuristic-designed and vanilla evolution-designed layouts.
With the rapid growth of the express industry, intelligent warehouses that employ autonomous robots for carrying parcels have been widely used to handle the vast express volume. For such warehouses, the warehouse layout design plays a key role in improving the transportation efficiency. However, this work is still done by human experts, which is expensive and leads to suboptimal results. In this paper, we aim to automate the warehouse layout designing process. We propose a two-layer evolutionary algorithm to efficiently explore the warehouse layout space, where an auxiliary objective fitness approximation model is introduced to predict the outcome of the designed warehouse layout and a two-layer population structure is proposed to incorporate the approximation model into the ordinary evolution framework. Empirical experiments show that our method can efficiently design effective warehouse layouts that outperform both heuristic-designed and vanilla evolution-designed warehouse layouts.