The field of routing and network optimization is witnessing significant developments, driven by the need for efficient and adaptive solutions. Researchers are exploring innovative approaches to address complex problems, such as local routing on geometric networks, vehicle routing, and network resilience. A key trend is the integration of machine learning and reinforcement learning techniques to improve the performance of routing algorithms. For instance, the use of edge-based transformers and graph neural networks is showing promise in solving vehicle routing problems and optimizing network flows. Additionally, there is a growing focus on developing resilient and adaptive data transmission protocols, as well as assessing the resilience of cyber-physical distribution power systems. Noteworthy papers in this area include EFormer, which introduces an effective edge-based transformer for vehicle routing problems, and JANUS, a resilient and adaptive data transmission approach for cross-facility scientific workflows. Overall, these advances are expected to have a significant impact on various fields, including logistics, transportation, and energy systems.
Advances in Routing and Network Optimization
Sources
Local Routing on Ordered $\Theta$-graphs
EFormer: An Effective Edge-based Transformer for Vehicle Routing Problems
Reinforcement learning for hybrid charging stations planning and operation considering fixed and mobile chargers
Robust Dynamic Material Handling via Adaptive Constrained Evolutionary Reinforcement Learning
Minimal Per-Flow Backlog Bounds at an Aggregate FIFO Server under Piecewise-Linear Arrival Curves
JANUS: Resilient and Adaptive Data Transmission for Enabling Timely and Efficient Cross-Facility Scientific Workflows
Resilience assessment framework for cyber-physical distribution power system based on coordinated cyber-physical attacks under dynamic game
On the Age of Information in Single-Server Queues with Aged Updates
Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks
Automated Generation of Diverse Courses of Actions for Multi-Agent Operations using Binary Optimization and Graph Learning
Smart Ride and Delivery Services with Electric Vehicles: Leveraging Bidirectional Charging for Profit Optimisation
Demonstration of effective UCB-based routing in skill-based queues on real-world data
Flowcut Switching: High-Performance Adaptive Routing with In-Order Delivery Guarantees