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
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Online Access:http://umpir.ump.edu.my/id/eprint/26094/1/An%20experimental%20study%20of%20modified%20black%20hole%20algorithms.wm.pdf
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spelling my-ump-ir.260942023-03-02T07:23:53Z An experimental study of modified black hole algorithms 2018-10 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 http://umpir.ump.edu.my/id/eprint/26094/ http://umpir.ump.edu.my/id/eprint/26094/1/An%20experimental%20study%20of%20modified%20black%20hole%20algorithms.wm.pdf pdf en public https://efind.ump.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=7978 phd doctoral Universiti Malaysia Pahang Faculty of Manufacturing Engineering Ibrahim, Zuwairie
institution Universiti Malaysia Pahang Al-Sultan Abdullah
collection UMPSA Institutional Repository
language English
advisor Ibrahim, Zuwairie
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
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
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
granting_institution Universiti Malaysia Pahang
granting_department Faculty of Manufacturing Engineering
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/26094/1/An%20experimental%20study%20of%20modified%20black%20hole%20algorithms.wm.pdf
_version_ 1783732103049904128