This research topic explores the theoretical foundations and practical applications of graph labeling and coloring problems, both of which are central to modern combinatorics and computer science.

This project implements six graph coloring algorithms — ranging from simple greedy heuristics to a customized, improved Genetic Algorithm (GA). The goal is to show how heuristic design strongly ...

Abstract: This study provided molecular solutions for the graph coloring problems (GCP) by two steps: (1) translating vertices to strands and (2) generating DNA procedures. At the first step, we ...

A timetable can be thought of as an assignment of timeslots to different events in any institution. So, we made this simple “Scheduling of Class timetable using Graph Coloring” where each color ...

The problem of compiling general quantum algorithms for implementation on near-term quantum processors has been introduced to the AI community. Previous work demonstrated that temporal planning is an ...

Abstract: Among the limitations of current quantum machines, the qubits count represents one of the most critical challenges for porting reasonably large computational problems, such as those coming ...

Let G be a graph and k a natural number. A k-coloring of G is a map c that maps the vertices of G into the set {1, 2, ..., k} (whose elements are called colors) such that no two adjacent vertices are ...