An application of deep reinforcement learning and vendor-managed inventory in perishable supply chain management

N Mohamadi, STA Niaki, M Taher… - Engineering Applications of …, 2024 - Elsevier
This article delves into the challenging supply chain management domain, explicitly
addressing the intricate issue of perishable inventory allocation within a two-echelon supply …

Data-driven dynamic pricing and inventory management of an omni-channel retailer in an uncertain demand environment

S Liu, J Wang, R Wang, Y Zhang, Y Song… - Expert Systems with …, 2024 - Elsevier
In recent years, omni-channel retailing has become immensely popular among both retailers
and consumers. In this approach, retailers often leverage their brick-and-mortar stores to …

Deep Reinforcement Learning Algorithms for Dynamic Pricing and Inventory Management of Perishable Products

T Yavuz, O Kaya - Applied Soft Computing, 2024 - Elsevier
ABSTRACT A perishable product has a limited shelf life, and inefficient management often
leads to waste. This paper focuses on dynamic pricing and inventory management …

A proximal policy optimization approach for food delivery problem with reassignment due to order cancellation

Y Deng, Y Yan, AHF Chow, Z Zhou, C Ying… - Expert Systems with …, 2024 - Elsevier
Unexpected cancellation of food delivery orders poses significant challenges to resource
allocation planning and could lead to reduced revenue for service providers. This paper …

Dynamic replenishment policy for perishable goods using change point detection-based soft actor-critic reinforcement learning

A Kou, Y Cheng, X Huang, J ** - Expert Systems with Applications, 2025 - Elsevier
This paper examines the problem of establishing a dynamic replenishment policy that
minimizes the costs associated with selling perishable goods. The perishable inventory is …

Reinforcement Learning for Dynamic Pricing under Competition for Perishable Products

SB Gadipudi, RK Kalaimani - 2024 28th International …, 2024 - ieeexplore.ieee.org
Dynamic pricing strategies, which adapt prices based on external influences, have gained
prominence in various industries. This approach involves frequent adjustments in response …

Reinforcement learning for dynamic pricing and capacity allocation in monetized customer wait-skip** services

C Garcia - Journal of Business Analytics, 2024 - Taylor & Francis
We consider how to facilitate a dynamically-priced premium service option that enables
customer parties to shorten their wait in a queue. Offering such a service requires that some …

Sustainable supply chain management: A green computing approach using deep Q-networks

D Yuan, Y Wang - Sustainable Computing: Informatics and Systems, 2025 - Elsevier
This paper addresses the challenges of resource allocation and inventory management in
supply chain systems by constructing an intelligent supply chain optimization model based …

By Fair Means or Foul: Quantifying Collusion in a Market Simulation with Deep Reinforcement Learning

M Schlechtinger, D Kosack, F Krause… - arxiv preprint arxiv …, 2024 - arxiv.org
In the rapidly evolving landscape of eCommerce, Artificial Intelligence (AI) based pricing
algorithms, particularly those utilizing Reinforcement Learning (RL), are becoming …

Collaborating in a competitive world: Heterogeneous Multi-Agent Decision Making in Symbiotic Supply Chain Environments

W Wang, H Wang, AJ Sobey - arxiv preprint arxiv:2501.14111, 2025 - arxiv.org
Supply networks require collaboration in a competitive environment. To achieve this, nodes
in the network often form symbiotic relationships as they can be adversely effected by the …