A novel clustering based genetic algorithm for route optimization

Genetic Algorithm (GA), a random universal evolutionary search technique that imitates the principle of biological evolution has been applied in solving various problems in different fields of human endeavor. Despite it strength and wide range of applications, optimal solution may not be feasible in...

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Main Authors:	Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe
Format:	Article
Language:	English English English
Published:	Elsevier B.V. 2016
Subjects:	T10.5 Communication of technical information
Online Access:	http://irep.iium.edu.my/52191/ http://irep.iium.edu.my/52191/ http://irep.iium.edu.my/52191/ http://irep.iium.edu.my/52191/3/52191_A%20novel%20clustering%20based%20genetic%20algorithm%20for%20route%20optimization_pdf.pdf http://irep.iium.edu.my/52191/4/52191_A%20novel%20clustering%20based%20genetic%20algorithm%20for%20route%20optimization_wos.pdf http://irep.iium.edu.my/52191/15/52191_A%20novel%20Clustering%20based%20Genetic_SCOPUS.pdf

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spelling	iium-521912019-06-26T01:12:59Z http://irep.iium.edu.my/52191/ A novel clustering based genetic algorithm for route optimization Aibinu, Abiodun Musa Salau, Habeeb Bello Najeeb, Athaur Rahman Nwohu, Mark Ndubuka Akachukwu, Chichebe T10.5 Communication of technical information Genetic Algorithm (GA), a random universal evolutionary search technique that imitates the principle of biological evolution has been applied in solving various problems in different fields of human endeavor. Despite it strength and wide range of applications, optimal solution may not be feasible in situations where reproduction processes which involve chromosomes selection for mating and regeneration are not properly done. In addition, difficulty is often encountered when there are significant differences in the fitness values of chromosomes while using probabilistic based selection approach. In this work, clustering based GA with polygamy and dynamic population control mechanism have been proposed. Fitness value obtained from chromosomes in each generation were clustered into two-non-overlapping clusters. The surviving chromosomes in the selected cluster were subjected to polygamy crossover mating process while the population of the offsprings which would form the next generation were subjected to dynamic population control mechanisms. The process was repeated until convergence to global solution was achieved or number of generation elapsed. The proposed algorithm has been applied to route optimization problem. Results obtained showed that the proposed algorithm outperforms some of the existing techniques. Furthermore, the proposed algorithm converged to global solution within few iterations (generations) thus favoring its acceptability for online-realtime applications. It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. In addition, the introduction of dynamic population control with polygamy selection processes enabled fast convergence to optimal solution and diversity in the population respectively. Elsevier B.V. 2016-08-21 Article NonPeerReviewed application/pdf en http://irep.iium.edu.my/52191/3/52191_A%20novel%20clustering%20based%20genetic%20algorithm%20for%20route%20optimization_pdf.pdf application/pdf en http://irep.iium.edu.my/52191/4/52191_A%20novel%20clustering%20based%20genetic%20algorithm%20for%20route%20optimization_wos.pdf application/pdf en http://irep.iium.edu.my/52191/15/52191_A%20novel%20Clustering%20based%20Genetic_SCOPUS.pdf Aibinu, Abiodun Musa and Salau, Habeeb Bello and Najeeb, Athaur Rahman and Nwohu, Mark Ndubuka and Akachukwu, Chichebe (2016) A novel clustering based genetic algorithm for route optimization. Engineering Science and Technology, an International Journal, 19 (4). pp. 2022-2034. ISSN 2215-0986 http://www.sciencedirect.com/science/article/pii/S2215098616300738 10.1016/j.jestch.2016.08.003
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English English
topic	T10.5 Communication of technical information
spellingShingle	T10.5 Communication of technical information Aibinu, Abiodun Musa Salau, Habeeb Bello Najeeb, Athaur Rahman Nwohu, Mark Ndubuka Akachukwu, Chichebe A novel clustering based genetic algorithm for route optimization
description	Genetic Algorithm (GA), a random universal evolutionary search technique that imitates the principle of biological evolution has been applied in solving various problems in different fields of human endeavor. Despite it strength and wide range of applications, optimal solution may not be feasible in situations where reproduction processes which involve chromosomes selection for mating and regeneration are not properly done. In addition, difficulty is often encountered when there are significant differences in the fitness values of chromosomes while using probabilistic based selection approach. In this work, clustering based GA with polygamy and dynamic population control mechanism have been proposed. Fitness value obtained from chromosomes in each generation were clustered into two-non-overlapping clusters. The surviving chromosomes in the selected cluster were subjected to polygamy crossover mating process while the population of the offsprings which would form the next generation were subjected to dynamic population control mechanisms. The process was repeated until convergence to global solution was achieved or number of generation elapsed. The proposed algorithm has been applied to route optimization problem. Results obtained showed that the proposed algorithm outperforms some of the existing techniques. Furthermore, the proposed algorithm converged to global solution within few iterations (generations) thus favoring its acceptability for online-realtime applications. It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. In addition, the introduction of dynamic population control with polygamy selection processes enabled fast convergence to optimal solution and diversity in the population respectively.
format	Article
author	Aibinu, Abiodun Musa Salau, Habeeb Bello Najeeb, Athaur Rahman Nwohu, Mark Ndubuka Akachukwu, Chichebe
author_facet	Aibinu, Abiodun Musa Salau, Habeeb Bello Najeeb, Athaur Rahman Nwohu, Mark Ndubuka Akachukwu, Chichebe
author_sort	Aibinu, Abiodun Musa
title	A novel clustering based genetic algorithm for route optimization
title_short	A novel clustering based genetic algorithm for route optimization
title_full	A novel clustering based genetic algorithm for route optimization
title_fullStr	A novel clustering based genetic algorithm for route optimization
title_full_unstemmed	A novel clustering based genetic algorithm for route optimization
title_sort	novel clustering based genetic algorithm for route optimization
publisher	Elsevier B.V.
publishDate	2016
url	http://irep.iium.edu.my/52191/ http://irep.iium.edu.my/52191/ http://irep.iium.edu.my/52191/ http://irep.iium.edu.my/52191/3/52191_A%20novel%20clustering%20based%20genetic%20algorithm%20for%20route%20optimization_pdf.pdf http://irep.iium.edu.my/52191/4/52191_A%20novel%20clustering%20based%20genetic%20algorithm%20for%20route%20optimization_wos.pdf http://irep.iium.edu.my/52191/15/52191_A%20novel%20Clustering%20based%20Genetic_SCOPUS.pdf
first_indexed	2023-09-18T21:13:59Z
last_indexed	2023-09-18T21:13:59Z
_version_	1777411439196110848

A novel clustering based genetic algorithm for route optimization

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