Nature

Vehicle Routing Optimization and Algorithms

Vehicle routing optimisation encompasses a range of mathematical and computational strategies aimed at determining the most efficient routes for vehicle fleets. This field addresses challenges such as ...
EurekAlert!

New survey explores deep learning-based algorithms for the traveling salesman problem

Recent survey delivers the first systematic benchmark of TSP solvers spanning end-to-end deep learners, hybrid methods and brand-new LLM-based hybrids, revealing that hybrids give best-in-class routes ...
IEEE

CoQGR: A collaborative routing strategy integrating Q-learning and cooperative game theory for large-scale LEO satellite constellations

Abstract: Traditional routing techniques face considerable challenges in large-scale Low Earth Orbit (LEO) satellite networks for Internet of Things (IoT) data backhaul, such as slow convergence speed ...
IEEE

Toward the Age in Forwarding: A Deep Reinforcement Learning Enabled Routing Mechanism for Large-Scale Satellite Networks via Spatial–Temporal Graph Neural Networks

Abstract: In large-scale satellite networks, end-to-end data delivery confronts long propagation latency and dynamical connectivity, heavily challenging current routing strategies due to the ...
GitHub

dynamic-moe-router-kit

dynamic-moe-router-kit implements adaptive expert routing for Mixture-of-Experts (MoE) models, dynamically selecting the optimal number of experts per token based on input complexity. Based on the ...