A more efficient way of finding Hamiltonian cycle

TL;DR

This paper introduces an improved algorithm for finding Hamiltonian cycles by analyzing original and opposite graphs to efficiently eliminate unnecessary edges and prioritize promising paths, reducing computational effort.

Contribution

The paper presents a novel algorithm that enhances Hamiltonian cycle detection by leveraging graph analysis to prune edges and optimize search paths.

Findings

Algorithm effectively reduces search space by removing unnecessary edges.

It improves detection efficiency compared to traditional methods.

Prioritizes promising paths over exhaustive search.

Abstract

In order to find Hamiltonian cycle, algorithm should find edges that creates a Hamiltonian cycle. Higher number of edges creates more possibilities to check to solve the problem. Algorithm rests on analysis of original graph and opposite graph to it. Algorithm can remove unnecessary edges from graph and test when Hamiltonian cycle can't exist in graph. Algorithm prefers "to think over" which paths should be checked than check many wrong paths.