Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection

Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. These algorithms belong to stochastic and nondeterministic classes, have some problems with exploration or exploitation. The researchers used different strategies to tackle these issues. The...

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Main Author:	Iqbal, Muhammad
Format:	Thesis
Language:	English English English
Published:	2023
Subjects:	T Technology (General)
Online Access:	http://eprints.uthm.edu.my/11046/1/24p%20MUHAMMAD%20IQBAL.pdf http://eprints.uthm.edu.my/11046/2/MUHAMMAD%20IQBAL%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/11046/3/MUHAMMAD%20IQBAL%20WATERMARK.pdf
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id	my-uthm-ep.11046
record_format	uketd_dc
spelling	my-uthm-ep.110462024-05-29T02:26:53Z Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection 2023-03 Iqbal, Muhammad T Technology (General) Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. These algorithms belong to stochastic and nondeterministic classes, have some problems with exploration or exploitation. The researchers used different strategies to tackle these issues. The flower pollination algorithm (FPA) is one of the more popular nature-inspired search algorithms. It has powerful global searchability to find the best optimal solution of real-world problems by using levy flight to explore the search space. Moreover, its single tuning parameter and simple mathematical model make it easier to implement. However, the flower pollination algorithm has a few drawbacks which are partially addressed by the practitioners. The first issue is regarding the balance between global pollination and local pollination, which may negatively affect the optimality of solution. Secondly, the FPA has a diversification problem which may leads to premature convergence of the optimal solution. This research proposed an algorithm which is based on dynamic switch probability to control the balance between exploration and exploitation which increases its searchability. The swap operator has been added in local pollination to enhance the exploitation behavior of pollens during the pollination process. Furthermore, it is hybridized with the Pattern Search algorithm to ensure the optimality of the solution. The performance of the proposed algorithm (IFPDSO-PS) has been evaluated on seventeen standard test functions and compared with the stated metaheuristic algorithms. The statistical tools (Absolute Mean Error & Fried Man) are used to rank the performance of all algorithms. The proposed algorithm is ranked first among the stated algorithms with respect to its performance in getting the optimal solution 2023-03 Thesis http://eprints.uthm.edu.my/11046/ http://eprints.uthm.edu.my/11046/1/24p%20MUHAMMAD%20IQBAL.pdf text en public http://eprints.uthm.edu.my/11046/2/MUHAMMAD%20IQBAL%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/11046/3/MUHAMMAD%20IQBAL%20WATERMARK.pdf text en validuser phd doctoral Universiti Tun Hussein Onn Malaysia Fakulti Sains Komputer dan Teknologi Maklumat
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	T Technology (General)
spellingShingle	T Technology (General) Iqbal, Muhammad Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
description	Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. These algorithms belong to stochastic and nondeterministic classes, have some problems with exploration or exploitation. The researchers used different strategies to tackle these issues. The flower pollination algorithm (FPA) is one of the more popular nature-inspired search algorithms. It has powerful global searchability to find the best optimal solution of real-world problems by using levy flight to explore the search space. Moreover, its single tuning parameter and simple mathematical model make it easier to implement. However, the flower pollination algorithm has a few drawbacks which are partially addressed by the practitioners. The first issue is regarding the balance between global pollination and local pollination, which may negatively affect the optimality of solution. Secondly, the FPA has a diversification problem which may leads to premature convergence of the optimal solution. This research proposed an algorithm which is based on dynamic switch probability to control the balance between exploration and exploitation which increases its searchability. The swap operator has been added in local pollination to enhance the exploitation behavior of pollens during the pollination process. Furthermore, it is hybridized with the Pattern Search algorithm to ensure the optimality of the solution. The performance of the proposed algorithm (IFPDSO-PS) has been evaluated on seventeen standard test functions and compared with the stated metaheuristic algorithms. The statistical tools (Absolute Mean Error & Fried Man) are used to rank the performance of all algorithms. The proposed algorithm is ranked first among the stated algorithms with respect to its performance in getting the optimal solution
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Iqbal, Muhammad
author_facet	Iqbal, Muhammad
author_sort	Iqbal, Muhammad
title	Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
title_short	Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
title_full	Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
title_fullStr	Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
title_full_unstemmed	Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
title_sort	improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Sains Komputer dan Teknologi Maklumat
publishDate	2023
url	http://eprints.uthm.edu.my/11046/1/24p%20MUHAMMAD%20IQBAL.pdf http://eprints.uthm.edu.my/11046/2/MUHAMMAD%20IQBAL%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/11046/3/MUHAMMAD%20IQBAL%20WATERMARK.pdf
_version_	1804890141460791296

Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection

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