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 ...
IEEE

Vehicle Routing Incorporating Implicit Preferences: An Omnidimensional Human–Algorithm Collaboration Approach

Due to the complexity and dynamism of real-world needs, traditional vehicle routing solutions usually do not sufficiently consider implicit user preferences, leading to low acceptance and reduced ...
Hackaday

Tolerating Delay With DTN

The Internet has spoiled us. You assume network packets either show up pretty quickly or they are never going to show up.
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 ...
marktechpost

Meet LLMRouter: An Intelligent Routing System designed to Optimize LLM Inference by Dynamically Selecting the most Suitable Model for Each Query

LLMRouter is an open source routing library from the U Lab at the University of Illinois Urbana Champaign that treats model selection as a first class system problem. It sits between applications and ...
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 ...