Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem

Sine Cosine Algorithm (SCA) is a population-based metaheuristic method that widely used to solve various optimization problem due to its ability in stabilizing between exploration and exploitation. However, SCA is rarely used to solve discrete optimization problem such as Quadratic Assignment Proble...

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Main Author:	Nurdiyana, Jamil
Format:	Thesis
Language:	eng eng
Published:	2022
Subjects:	Q Science (General)
Online Access:	https://etd.uum.edu.my/10448/1/s825969_01.pdf https://etd.uum.edu.my/10448/2/s825969_02.pdf
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spelling	my-uum-etd.104482023-03-30T01:22:36Z Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem 2022 Nurdiyana, Jamil Abdul Rahman, Syariza Benjamin, Aida Mauziah Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduates School of Arts & Sciences Q Science (General) Sine Cosine Algorithm (SCA) is a population-based metaheuristic method that widely used to solve various optimization problem due to its ability in stabilizing between exploration and exploitation. However, SCA is rarely used to solve discrete optimization problem such as Quadratic Assignment Problem (QAP) due to the nature of its solution which produce continuous values and makes it challenging in solving discrete optimization problem. The SCA is also found to be trapped in local optima since its lacking in memorizing the moves. Besides, local search strategy is required in attaining superior results and it is usually designed based on the problem under study. Hence, this study aims to develop a hybrid modified SCA with Tabu Search (MSCA-TS) model to solve QAP. In QAP, a set of facilities is assigned to a set of locations to form a one-to-one assignment with minimum assignment cost. Firstly, the modified SCA (MSCA) model with cost-based local search strategy is developed. Then, the MSCA is hybridized with TS to prohibit revisiting the previous solutions. Finally, both designated models (MSCA and MSCA-TS) were tested on 60 QAP instances from QAPLIB. A sensitivity analysis is also performed to identify suitable parameter settings for both models. Comparison of results shows that MSCA-TS performs better than MSCA. The percentage of error and standard deviation for MSCA-TS are lower than the MSCA which are 2.4574 and 0.2968 respectively. The computational results also shows that the MSCA-TS is an effective and superior method in solving QAP when compared to the best-known solutions presented in the literature. The developed models may assist decision makers in searching the most suitable assignment for facilities and locations while minimizing cost. 2022 Thesis https://etd.uum.edu.my/10448/ https://etd.uum.edu.my/10448/1/s825969_01.pdf text eng 2025-08-16 staffonly https://etd.uum.edu.my/10448/2/s825969_02.pdf text eng public other masters Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Abdul Rahman, Syariza Benjamin, Aida Mauziah
topic	Q Science (General)
spellingShingle	Q Science (General) Nurdiyana, Jamil Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem
description	Sine Cosine Algorithm (SCA) is a population-based metaheuristic method that widely used to solve various optimization problem due to its ability in stabilizing between exploration and exploitation. However, SCA is rarely used to solve discrete optimization problem such as Quadratic Assignment Problem (QAP) due to the nature of its solution which produce continuous values and makes it challenging in solving discrete optimization problem. The SCA is also found to be trapped in local optima since its lacking in memorizing the moves. Besides, local search strategy is required in attaining superior results and it is usually designed based on the problem under study. Hence, this study aims to develop a hybrid modified SCA with Tabu Search (MSCA-TS) model to solve QAP. In QAP, a set of facilities is assigned to a set of locations to form a one-to-one assignment with minimum assignment cost. Firstly, the modified SCA (MSCA) model with cost-based local search strategy is developed. Then, the MSCA is hybridized with TS to prohibit revisiting the previous solutions. Finally, both designated models (MSCA and MSCA-TS) were tested on 60 QAP instances from QAPLIB. A sensitivity analysis is also performed to identify suitable parameter settings for both models. Comparison of results shows that MSCA-TS performs better than MSCA. The percentage of error and standard deviation for MSCA-TS are lower than the MSCA which are 2.4574 and 0.2968 respectively. The computational results also shows that the MSCA-TS is an effective and superior method in solving QAP when compared to the best-known solutions presented in the literature. The developed models may assist decision makers in searching the most suitable assignment for facilities and locations while minimizing cost.
format	Thesis
qualification_name	other
qualification_level	Master's degree
author	Nurdiyana, Jamil
author_facet	Nurdiyana, Jamil
author_sort	Nurdiyana, Jamil
title	Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem
title_short	Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem
title_full	Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem
title_fullStr	Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem
title_full_unstemmed	Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem
title_sort	hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2022
url	https://etd.uum.edu.my/10448/1/s825969_01.pdf https://etd.uum.edu.my/10448/2/s825969_02.pdf
_version_	1776103819089805312

Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem

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