Nature

Graph Coloring Algorithms and Optimization Techniques

The graph colouring problem, a classic NP-hard challenge, is central to many practical applications such as scheduling, resource allocation and network management. Recent advances have seen the ...
Nature

B-Chromatic Number and Graph Coloring

The study of graph colouring has long been a central topic in discrete mathematics, with a prominent focus on optimising the assignment of labels or colours to vertices such that adjacent vertices are ...
Analytics Insight

10 Common Matplotlib Mistakes Beginners Make and How to Fix Them

Overview: Matplotlib mistakes often come from poor layout, unclear labels, and wrong scale choices, not from the data itself.Clear plotting improves when scatte ...
IEEE

Combining Reinforcement Learning and Heuristic Optimization: A Model Based on a Deep Q-Network and Graph Neural Networks for Graph Coloring

Abstract: We present a hybrid approach combining Reinforcement Learning (RL) with the TabuCol, which is a version of tabu search specifically designed for the Graph Coloring Problem (GCP), enhanced by ...
IEEE

Stochastic Geometry Analysis of Scalable Cell-Free RAN With Dynamic Association and Deployment

Abstract: Cell-free radio access network (CF-RAN) breaks away from the traditional cellular network, forming a scalable wireless access network structure. Based on the conventional cell-free massive ...
GitHub

CDAC-LABS_DSA-JAVA

This repository contains Data Structures and Algorithms (DSA) lab exercises implemented in Java as part of the CDAC curriculum. It covers fundamental problem-solving techniques, algorithmic complexity ...