An experimental study of modified black hole algorithms

Optimization is often required in many fields of research. Some systems are harder to optimize compared to others. For this reason, many meta-heuristic optimization methodshave been devised and improved. One of the meta-heuristic optimization methods is Black Hole (BH) algorithm, which is inspired b...

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Main Author:	Mohammed, Suad Khairi
Format:	Thesis
Language:	English
Published:	2018
Subjects:	QA Mathematics TS Manufactures
Online Access:	http://umpir.ump.edu.my/id/eprint/26094/ http://umpir.ump.edu.my/id/eprint/26094/ http://umpir.ump.edu.my/id/eprint/26094/1/An%20experimental%20study%20of%20modified%20black%20hole.pdf

id	ump-26094
recordtype	eprints
spelling	ump-260942019-10-18T03:43:32Z http://umpir.ump.edu.my/id/eprint/26094/ An experimental study of modified black hole algorithms Mohammed, Suad Khairi QA Mathematics TS Manufactures Optimization is often required in many fields of research. Some systems are harder to optimize compared to others. For this reason, many meta-heuristic optimization methodshave been devised and improved. One of the meta-heuristic optimization methods is Black Hole (BH) algorithm, which is inspired by the black hole in cosmology. The black hole has been found theoretically in the studies of the universe as a star having massive mass and gravity. The BH algorithm is a population-based method which uses more than one agent to find a solution in a search space. In BH algorithm, an agent with the best solution forms a black hole. The biggest mass is given to the agent with the best solution and other agents update their position towards the agent with the best solution. In this thesis, it is found that the BH algorithm suffers from premature convergence. Hence, three methods to prevent the premature convergence in BH algorithm are presented. The first method is the introduction of white hole operator. The white hole operator is proposed to avoid the agents from exploring the area near the worst agent. The second method is the application of a local search. Finally, a gravitational interaction, which is the essence of the gravitational search algorithm, is also applied. Ultimately, seven variants of BH algorithms are established based on the white hole, local search, and gravitational interaction. Those algorithms are Black Hole White Hole Algorithm, Gravitational Black Hole Algorithm, Gravitational Black Hole White Hole Algorithm, Black Hole Local Search Algorithm, Black Hole White Hole Local Search Algorithm, Gravitational Black Hole Local Search Algorithm, and Gravitational Black Hole White Hole Local Search Algorithm. The algorithms are evaluated based on unimodal, multimodal, hybrid, and composite functions in CEC2014 benchmark test functions. Benchmarking with particle swarm optimization (PSO), genetic algorithm (GA), and grey wolf optimizer (GWO) is done as well. Results show that all the variants are as good as PSO and better than the original BH algorithm. Statistical analysis suggests that one variant called Black Hole White Hole algorithm is the best since the Black Hole White Hole algorithm is significantly better than GA, GWO, and BH algorithms. 2018-10 Thesis NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26094/1/An%20experimental%20study%20of%20modified%20black%20hole.pdf Mohammed, Suad Khairi (2018) An experimental study of modified black hole algorithms. PhD thesis, Universiti Malaysia Pahang. https://efind.ump.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=7978
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA Mathematics TS Manufactures
spellingShingle	QA Mathematics TS Manufactures Mohammed, Suad Khairi An experimental study of modified black hole algorithms
description	Optimization is often required in many fields of research. Some systems are harder to optimize compared to others. For this reason, many meta-heuristic optimization methodshave been devised and improved. One of the meta-heuristic optimization methods is Black Hole (BH) algorithm, which is inspired by the black hole in cosmology. The black hole has been found theoretically in the studies of the universe as a star having massive mass and gravity. The BH algorithm is a population-based method which uses more than one agent to find a solution in a search space. In BH algorithm, an agent with the best solution forms a black hole. The biggest mass is given to the agent with the best solution and other agents update their position towards the agent with the best solution. In this thesis, it is found that the BH algorithm suffers from premature convergence. Hence, three methods to prevent the premature convergence in BH algorithm are presented. The first method is the introduction of white hole operator. The white hole operator is proposed to avoid the agents from exploring the area near the worst agent. The second method is the application of a local search. Finally, a gravitational interaction, which is the essence of the gravitational search algorithm, is also applied. Ultimately, seven variants of BH algorithms are established based on the white hole, local search, and gravitational interaction. Those algorithms are Black Hole White Hole Algorithm, Gravitational Black Hole Algorithm, Gravitational Black Hole White Hole Algorithm, Black Hole Local Search Algorithm, Black Hole White Hole Local Search Algorithm, Gravitational Black Hole Local Search Algorithm, and Gravitational Black Hole White Hole Local Search Algorithm. The algorithms are evaluated based on unimodal, multimodal, hybrid, and composite functions in CEC2014 benchmark test functions. Benchmarking with particle swarm optimization (PSO), genetic algorithm (GA), and grey wolf optimizer (GWO) is done as well. Results show that all the variants are as good as PSO and better than the original BH algorithm. Statistical analysis suggests that one variant called Black Hole White Hole algorithm is the best since the Black Hole White Hole algorithm is significantly better than GA, GWO, and BH algorithms.
format	Thesis
author	Mohammed, Suad Khairi
author_facet	Mohammed, Suad Khairi
author_sort	Mohammed, Suad Khairi
title	An experimental study of modified black hole algorithms
title_short	An experimental study of modified black hole algorithms
title_full	An experimental study of modified black hole algorithms
title_fullStr	An experimental study of modified black hole algorithms
title_full_unstemmed	An experimental study of modified black hole algorithms
title_sort	experimental study of modified black hole algorithms
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/26094/ http://umpir.ump.edu.my/id/eprint/26094/ http://umpir.ump.edu.my/id/eprint/26094/1/An%20experimental%20study%20of%20modified%20black%20hole.pdf
first_indexed	2023-09-18T22:40:25Z
last_indexed	2023-09-18T22:40:25Z
_version_	1777416877697400832

An experimental study of modified black hole algorithms

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