Ant colony system with heuristic function for the travelling salesman problem

Ant colony system which is classified as a meta-heuristic algorithm is considered as one of the best optimization algorithm for solving different type of NP-Hard problem including the travelling salesman problem.A heuristic function in the Ant colony system uses pheromone and distance values to prod...

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Main Authors: Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana
Format: Article
Language:English
Published: 2013
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/9849/1/J.pdf
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author Alobaedy, Mustafa Muwafak
Ku-Mahamud, Ku Ruhana
author_facet Alobaedy, Mustafa Muwafak
Ku-Mahamud, Ku Ruhana
author_sort Alobaedy, Mustafa Muwafak
collection UUM
description Ant colony system which is classified as a meta-heuristic algorithm is considered as one of the best optimization algorithm for solving different type of NP-Hard problem including the travelling salesman problem.A heuristic function in the Ant colony system uses pheromone and distance values to produce heuristic values in solving the travelling salesman problem.However, the heuristic values are not updated in the entire process to reflect the knowledge discovered by ants while moving from city to city. This paper presents the work on enhancing the heuristic function in ant colony system in order to reflect the new information discovered by the ants.Experimental results showed that enhanced algorithm provides better results than classical ant colony system in term of best, average and standard of the best tour length.
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spelling uum-98492013-12-24T02:53:04Z https://repo.uum.edu.my/id/eprint/9849/ Ant colony system with heuristic function for the travelling salesman problem Alobaedy, Mustafa Muwafak Ku-Mahamud, Ku Ruhana QA76 Computer software Ant colony system which is classified as a meta-heuristic algorithm is considered as one of the best optimization algorithm for solving different type of NP-Hard problem including the travelling salesman problem.A heuristic function in the Ant colony system uses pheromone and distance values to produce heuristic values in solving the travelling salesman problem.However, the heuristic values are not updated in the entire process to reflect the knowledge discovered by ants while moving from city to city. This paper presents the work on enhancing the heuristic function in ant colony system in order to reflect the new information discovered by the ants.Experimental results showed that enhanced algorithm provides better results than classical ant colony system in term of best, average and standard of the best tour length. 2013 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/9849/1/J.pdf Alobaedy, Mustafa Muwafak and Ku-Mahamud, Ku Ruhana (2013) Ant colony system with heuristic function for the travelling salesman problem. Journal of Next Generation Information Technology, 4 (2). pp. 39-48. ISSN 2092-8637 http://dx.doi.org/10.4156/jnit.vol4.issue2.5 doi:10.4156/jnit.vol4.issue2.5 doi:10.4156/jnit.vol4.issue2.5
spellingShingle QA76 Computer software
Alobaedy, Mustafa Muwafak
Ku-Mahamud, Ku Ruhana
Ant colony system with heuristic function for the travelling salesman problem
title Ant colony system with heuristic function for the travelling salesman problem
title_full Ant colony system with heuristic function for the travelling salesman problem
title_fullStr Ant colony system with heuristic function for the travelling salesman problem
title_full_unstemmed Ant colony system with heuristic function for the travelling salesman problem
title_short Ant colony system with heuristic function for the travelling salesman problem
title_sort ant colony system with heuristic function for the travelling salesman problem
topic QA76 Computer software
url https://repo.uum.edu.my/id/eprint/9849/1/J.pdf
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AT kumahamudkuruhana antcolonysystemwithheuristicfunctionforthetravellingsalesmanproblem