Learning Towards Fair Order Dispatching via Hierarchical Attention-based Reinforcement Learning for Garment Manufacturing
Year: 2025
Type: article
Abstract: Garment production represents a typical form of social manufacturing, where orders are received centrally but processed in a decentralized manner. Factories are equipped with different processing capabilities that cater to highly tailored demands. Despite extensive research on production order allocation, the changeover costs in garment manufacturing and the fairness of earnings among factories remain largely neglected. This paper proposes Hierarchical Attention-based reinforcement learning for order dispatching in garment production. In this paper, we propose Hierarchical Attention-based reinforcement learning for order dispatching in garment production. Specifically, a novel Hierarchical Attention Network is introduced to model the complex relationships between factories and orders, as well as the long-term income fairness of factories. Finally, the proposed method is deployed on the Cyber-Physical Internet.
Source: IFAC-PapersOnLine
Authors: Yanying Wang, Zhiheng Zhao, George Q. Huang
Institution: Hong Kong Polytechnic University
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4414567856