13 citations · 24 across the 4 of their papers we have counts for
4 papers
DeepStock: Reinforcement Learning with Policy Regularizations for Inventory Management
Yaqi Xie, Xinru Hao, Jiaxi Liu +4
Deep Reinforcement Learning (DRL) provides a general-purpose methodology for training inventory policies that can leverage big data and compute. However, off-the-shelf implementati…
A Deep Q-Network Based on Radial Basis Functions for Multi-Echelon Inventory Management
Liqiang Cheng, Jun Luo, Weiwei Fan +2
This paper addresses a multi-echelon inventory management problem with a complex network topology where deriving optimal ordering decisions is difficult. Deep reinforcement learnin…
Dynamic Pricing on E-commerce Platform with Deep Reinforcement Learning: A Field Experiment
Jiaxi Liu, Yidong Zhang, Xiaoqing Wang +2
In this paper we present an end-to-end framework for addressing the problem of dynamic pricing (DP) on E-commerce platform using methods based on deep reinforcement learning (DRL).…
Context-Based Dynamic Pricing with Online Clustering
Sentao Miao, Xi Chen, Xiuli Chao +2
We consider a context-based dynamic pricing problem of online products, which have low sales. Sales data from Alibaba, a major global online retailer, illustrate the prevalence of…