Evolving A* to Efficiently Solve the k Shortest-Path Problem (Extended Version)

TL;DR

This paper presents an evolved version of the A* algorithm that efficiently computes multiple shortest paths in a graph, significantly outperforming existing methods in various test scenarios.

Contribution

It introduces a new search algorithm derived from A* that maintains its properties while achieving the same time complexity for the k shortest paths problem.

Findings

Significant performance improvements over existing algorithms

Often achieves one or two orders of magnitude faster results

Applicable to many domains due to preserved properties

Abstract

The problem of finding the shortest path in a graph G(V, E) has been widely studied. However, in many applications it is necessary to compute an arbitrary number of them, k. Even though the problem has raised a lot of interest from different research communities and many applications of it are known, it has not been addressed to the same extent as the single shortest path problem. The best algorithm known for efficiently solving this task has a time complexity of O (|E| + |V|log{|V|}+k|V|)$ when computing paths in explicit form, and is based on best-first search. This paper introduces a new search algorithm with the same time complexity, which results from a natural evolution of A* thus, it preserves all its interesting properties, making it widely applicable to many different domains. Experiments in various testbeds show a significant improvement in performance over the state of the art, often by one or two orders of magnitude.