Hamiltonian Graphs and the Traveling Salesman Problem
Dhananjay P. Mehendale

TL;DR
This paper introduces a new polynomial-time algorithm for solving the Traveling Salesman Problem using a novel characterization of Hamiltonian graphs and an ordered weighted adjacency list, with extensions to quantum algorithms for search problems.
Contribution
It presents a new characterization of Hamiltonian graphs and an exact polynomial-time algorithm for TSP, along with quantum algorithms for unstructured search and K-SAT problems.
Findings
The algorithm finds shortest Hamiltonian paths and circuits efficiently.
A new characterization of shortest Hamiltonian tours under triangle inequality.
Quantum algorithms significantly improve search capabilities in NP-complete problems.
Abstract
A new characterization of Hamiltonian graphs using f-cutset matrix is proposed. Based on this new characterization, a new exact polynomial time algorithm for the traveling salesman problem (TSP) is developed. We then define the so-called ordered weighted adjacency list for given weighted complete graph and proceed to the paper's main result, namely, the exact algorithm based on the utilization of the ordered weighted adjacency list and the simple properties that any path or circuit must satisfy. This algorithm performs checking of sub-lists, containing (p-1) entries (edge pairs) for paths and p entries (edge pairs) for circuits, chosen from ordered adjacency list in a well defined sequence to determine exactly the shortest Hamiltonian path and shortest Hamiltonian circuit in a weighted complete graph of p vertices. The procedure has intrinsic advantage of landing on the desired solution…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Complexity and Algorithms in Graphs · Advanced Graph Theory Research
