IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 9, No 2: June 2020

A hybrid technique for single-source shortest path-based on A* algorithm and ant colony optimization

Sameer Alani (Al-Kitab University College)
Atheer Baseel (University of Anbar)
Mustafa Maad Hamdi (Universiti Tun Hussein Onn Malaysia)
Sami Abduljabbar Rashid (Al-Maarif university college)



Article Info

Publish Date
01 Jun 2020

Abstract

In the single-source shortest path (SSSP) problem, the shortest paths from a source vertex v to all other vertices in a graph should be executed in the best way. A common algorithm to solve the (SSSP) is the A* and Ant colony optimization (ACO). However, the traditional A* is fast but not accurate because it doesn’t calculate all node's distance of the graph. Moreover, it is slow in path computation. In this paper, we propose a new technique that consists of a hybridizing of A* algorithm and ant colony optimization (ACO). This solution depends on applying the optimization on the best path. For justification, the proposed algorithm has been applied to the parking system as a case study to validate the proposed algorithm performance. First, A*algorithm generates the shortest path in fast time processing. ACO will optimize this path and output the best path. The result showed that the proposed solution provides an average decreasing time performance is 13.5%.

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Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...