Identifying the Shortest Path in Large Networks using Boolean Satisfiability (original) (raw)

A Novel Solution for Simultaneously Finding the Shortest and Possible Paths in Complex Networks

2019

A Novel graph approach named Combined Forward and Backward Heuristic Search (CFBHS) is proposed in this paper, which can be used to solve optimization problems in areas such as transportation and network routing. There are two major aspects distinct our method from the most cited ones. Firstly, though focuses on getting the shortest path in a graph when both source and destination are given, this work can also find other possible paths as outputs. Secondly, the proposed algorithm is a high-performance one, which is achieved by (1) reducing unnecessary nodes and edges to reach a target optimum based on dynamically calculated heuristic values and (2) finding the results by using the sub-division scheme instead of computing over the whole graph. Experiments are carried out for the complex road network of Yangon Region. The comparisons show that our algorithm is about 100 times faster than the bi-directional Dijkstra’s algorithm. Besides, benefit from the heuristic forward and backward ...

Review and Performance Analysis of Shortest Path Problem Solving Algorithms

The International Journal on Advances in Software, ISSN: 1942-2628, vol. 7, no. 1& 2,year 2014,, 2014

The development of concepts derived from the generic approach to solving the problem of the shortest path resulted in numerous and various algorithms that appeared over the past decades. The studies on the most basic operation aimed at the determination of the shortest path between two given points in a graph (in other words, often a network) have resulted in sophisticated solutions designed for more and more demanding applications. Those include finding the sets of paths with the shortest distance between all pairs of nodes or searching for a shortest path tree. The aim of the present article is to give the reader an introduction to the problem of the shortest path and a detailed review of two groups of selected algorithms designed to solve particular problems. In the study described herein, different algorithms have been examined for their efficacy in their operation in directed graphs of different type represented in a well-defined data structure. The empirical simulation-based analysis proves that the performance varies among algorithms under investigation and allows to suggest, which methods ought to be used to solve specific variants of the shortest path problem and which algorithms should be avoided or used with caution.

Shortest Path Algorithms between Theory and Practice

MSc Thesis, 2019

Utilizing graph algorithms is a common activity in computer science. Algorithms that perform computations on large graphs are not always efficient. This work investigates the Single-Source Shortest Path (SSSP) problem, which is considered to be one of the most important and most studied graph problems. This thesis contains a review of the SSSP problem in both theory and practice. In addition, it discusses a new single-source shortest-path algorithm that achieves the same O(ncdotm)O(n \cdot m)O(ncdotm) time bound as the traditional Bellman-Ford-Moore algorithm but outperforms it and other state-of-the-art algorithms in practice. The work is comprised of three parts. The first discusses some basic shortest-path and negative-cycle-detection algorithms in literature from the theoretical and practical point of view. The second contains a discussion of a new algorithm for the single-source shortest-path problem that outperforms most state-of-the-art algorithms for several well-known families of graphs. The main idea behind the proposed algorithm is to select the fewest most-effective vertices to scan. We also propose a discussion of correctness, termination, and the proof of the worst-case time bound of the proposed algorithm. This section also suggests two different implementations for the proposed algorithm, the first runs faster while the second performs a fewer number of operations. Finally, an extensive computational study of the different shortest paths algorithms is conducted. The results are proposed using a new evaluation metric for shortest-path algorithms. A discussion of outcomes, strengths, and weaknesses of the various shortest path algorithms are also included in this work.

A Survey of Shortest-Path Algorithms

ArXiv, 2017

A shortest-path algorithm finds a path containing the minimal cost between two vertices in a graph. A plethora of shortest-path algorithms is studied in the literature that span across multiple disciplines. This paper presents a survey of shortest-path algorithms based on a taxonomy that is introduced in the paper. One dimension of this taxonomy is the various flavors of the shortest-path problem. There is no one general algorithm that is capable of solving all variants of the shortest-path problem due to the space and time complexities associated with each algorithm. Other important dimensions of the taxonomy include whether the shortest-path algorithm operates over a static or a dynamic graph, whether the shortest-path algorithm produces exact or approximate answers, and whether the objective of the shortest-path algorithm is to achieve time-dependence or is to only be goal directed. This survey studies and classifies shortest-path algorithms according to the proposed taxonomy. Th...