Solve For Shortest Paths Problem Within Logarithm Runtime

TL;DR

This paper introduces a novel approach combining database techniques with best-first-search to solve the Shortest Paths Problem efficiently, achieving logarithmic runtime on large-scale instances, which surpasses current methods in performance.

Contribution

The paper presents a new synthesis method integrating database modules with search algorithms to solve SPP in logarithmic time, demonstrating practical efficiency on large datasets.

Findings

Achieved logarithmic runtime for large-scale SPP instances.

Demonstrated robustness and practicality on transaction data.

Outperformed existing methods in efficiency and scalability.

Abstract

The Shortest Paths Problem (SPP) is no longer unresolved. Just for a large scalar of instance on this problem, even we cannot know if an algorithm achieves the computing. Those cutting-edge methods are still in the low performance. If we go to a strategy the best-first-search to deal with computing, it is awkward that the technical barrier from another field: the database, which with the capable of Online Oriented. In this paper, we will introduce such a synthesis to solve for SPP which comprises various modules therein including such database leads to finish the task in a logarithm runtime. Through experiments taken on three typical instances on mega-scalar data for transaction in a common laptop, we show off a totally robust, tractable and practical applicability for other projects.