Open AccessResearch on Autonomous Vehicle Storage and Retrieval System Cargo Location Optimization in E-commerce Automated Warehouse
Author(s) -
Haoxiang Wang,
Shouwen Ji,
G.H. Su
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/790/1/012165
Subject(s) - warehouse , computer science , automation , stability (learning theory) , software , matlab , genetic algorithm , computer data storage , database , engineering , operating system , mechanical engineering , marketing , machine learning , business
Cargo allocation optimization is important to improve the efficiency of e-commerce automated warehouse’s autonomous vehicle storage and retrieval system (AVS/RS) operations. Considering the electrical business logistics characteristic of small batch, batches, variety characteristics, this paper aiming at maximizing the highest efficiency and shelf stability for warehousing efficiency, we established an initial cargo location model, designed an adaptive multi-objective genetic algorithm. MATLAB software programming was used to implement the model solution, and an example verification was performed with an automation warehouse named Jing-dong in China. The comparison between the initial cargo location model and the random storage strategy shows that the model can significantly improve the overall warehousing efficiency and shelf stability of AVS/RS.