GitHub

GTA: Graph Theory Agent and Benchmark for Algorithmic Graph Reasoning with LLMs

This repository provides partial datasets and the automated code for generating graph problem instances as described in the paper "GTA: Graph Theory Agent and Benchmark for Algorithmic Graph Reasoning ...
Hackaday

Where Graph Theory Meets The Road: The Algorithms Behind Route Planning

Back in the hazy olden days of the pre-2000s, navigating between two locations generally required someone to whip out a paper map and painstakingly figure out the most optimal route between those ...
IEEE

Optimal graph design using a knowledge-driven multi-objective evolutionary graph algorithm

Abstract: Designing appropriate graphs is a problem frequently occurring in several common applications ranging from designing communication and transportation networks to discovering new drugs. More ...
IEEE

Deep Reinforcement Learning Using Graph Conv-LSTM for Solving Multi-Objective Combinatorial Optimization Problems

Abstract: This paper introduces MOGCL (Multi-Objective Graph Convolutional Long Short-Term Memory with Attention), a novel model that combines dynamic graph Convolutional Long Short-Term Memory ...