Reinforcement learning for logistics and supply chain management: Methodologies, state of the art, and future opportunities
With advances in technologies, data science techniques, and computing equipment, there
has been rapidly increasing interest in the applications of reinforcement learning (RL) to …
has been rapidly increasing interest in the applications of reinforcement learning (RL) to …
Analyzing the Implementation of Digital Twins in the Agri-Food Supply Chain
Background: Digital twins have the potential to significantly improve the efficiency and
sustainability of the agri-food supply chain by providing visibility, reducing bottlenecks …
sustainability of the agri-food supply chain by providing visibility, reducing bottlenecks …
Deep reinforcement learning for the dynamic and uncertain vehicle routing problem
W Pan, SQ Liu - Applied Intelligence, 2023 - Springer
Accurate and real-time tracking for real-world urban logistics has become a popular
research topic in the field of intelligent transportation. While the routing of urban logistic …
research topic in the field of intelligent transportation. While the routing of urban logistic …
Multiple-uav reinforcement learning algorithm based on improved ppo in ray framework
G Zhan, X Zhang, Z Li, L Xu, D Zhou, Z Yang - Drones, 2022 - mdpi.com
Distributed multi-agent collaborative decision-making technology is the key to general
artificial intelligence. This paper takes the self-developed Unity3D collaborative combat …
artificial intelligence. This paper takes the self-developed Unity3D collaborative combat …
[HTML][HTML] Container port truck dispatching optimization using Real2Sim based deep reinforcement learning
In marine container terminals, truck dispatching optimization is often considered as the
primary focus as it provides crucial synergy between the sea-side operations and yard-side …
primary focus as it provides crucial synergy between the sea-side operations and yard-side …
Investigating the consumption behavior of young adults using online food delivery platforms during the COVID-19 pandemic
Purpose Online food delivery has been prevalent in recent years worldwide, especially
during the COVID-19 pandemic, and people's consumption behaviors have changed …
during the COVID-19 pandemic, and people's consumption behaviors have changed …
A location-production-routing problem for distributed manufacturing platforms: A neural genetic algorithm solution methodology
Additive Manufacturing (AM) enhances the flexibility of manufacturing networks. In this
paper, we present a Location-Production-Routing (LPR) problem designed for a distributed …
paper, we present a Location-Production-Routing (LPR) problem designed for a distributed …
From click to cuisine: Unpacking the interplay of online food delivery services through barriers, trust, post-usage usefulness, and moral obligation
Online food delivery (OFD) has gained popularity because of rapid urbanization and busy
lifestyles of individuals in the last decade. Nevertheless, despite the surging fame and …
lifestyles of individuals in the last decade. Nevertheless, despite the surging fame and …
Reducing traffic violations in the online food delivery industry—A case study in Xi'an City, China
Online food delivery (OFD) is one of the top industries in the Online-to-offline (O2O)
commerce sector. Deliverymen need to complete a large number of delivery orders in limited …
commerce sector. Deliverymen need to complete a large number of delivery orders in limited …
A workload-balancing order dispatch scheme for O2O food delivery with order splitting choice
Online-to-offline (O2O) food delivery service refers to an emerging modern business model
that enables customers to order foods from local restaurants via an online platform, and then …
that enables customers to order foods from local restaurants via an online platform, and then …