Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function

Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function

The optimization algorithms that imitate nature have acquired much attention principally mechanisms for solving the difficult issues for example the travelling salesman problem (TSP) which is containing routing and scheduling of the tasks. This thesis presents the parallel Bees Algorithm as a new a...

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Main Author: Hammash, Nayif Mohammed
Format: Thesis
Language:eng
eng
Published: 2012
Subjects:
QA76 Computer software
Online Access:https://etd.uum.edu.my/2924/1/Nayif_Mohammed_Hammash.pdf
https://etd.uum.edu.my/2924/4/Nayif_Mohammed_Hammash.pdf
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record_format uketd_dc
institution Universiti Utara Malaysia
collection UUM ETD
language eng
eng
advisor Mahmuddin, Massudi
topic QA76 Computer software
spellingShingle QA76 Computer software
Hammash, Nayif Mohammed
Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
description The optimization algorithms that imitate nature have acquired much attention principally mechanisms for solving the difficult issues for example the travelling salesman problem (TSP) which is containing routing and scheduling of the tasks. This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. Bees Algorithm is one of the optimization algorithms inspired from the natural foraging ways of the honey bees of finding the best solution. It is a series of activities based on the searching algorithm in order to access the best solutions. It is an iteration algorithm; therefore, it is suffering from slow convergence. The other downside of the Bee Algorithm is that it has needless computation. This means that it spends a long time for the bees algorithm converge the optimum solution. In this study, the parallel bees algorithm technique is proposed for overcoming of this issue. Due to that, this would lead to reduce the required time to get a solution with faster results accuracy than original Bees Algorithm.
format Thesis
qualification_name masters
qualification_level Master's degree
author Hammash, Nayif Mohammed
author_facet Hammash, Nayif Mohammed
author_sort Hammash, Nayif Mohammed
title Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
title_short Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
title_full Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
title_fullStr Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
title_full_unstemmed Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
title_sort performance comparison of parallel bees algorithm on rosenbrock function
granting_institution Universiti Utara Malaysia
granting_department Awang Had Salleh Graduate School of Arts & Sciences
publishDate 2012
url https://etd.uum.edu.my/2924/1/Nayif_Mohammed_Hammash.pdf
https://etd.uum.edu.my/2924/4/Nayif_Mohammed_Hammash.pdf
_version_ 1747827462064046080
spelling my-uum-etd.29242016-04-27T01:44:34Z Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function 2012 Hammash, Nayif Mohammed Mahmuddin, Massudi Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts and Sciences QA76 Computer software The optimization algorithms that imitate nature have acquired much attention principally mechanisms for solving the difficult issues for example the travelling salesman problem (TSP) which is containing routing and scheduling of the tasks. This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. Bees Algorithm is one of the optimization algorithms inspired from the natural foraging ways of the honey bees of finding the best solution. It is a series of activities based on the searching algorithm in order to access the best solutions. It is an iteration algorithm; therefore, it is suffering from slow convergence. The other downside of the Bee Algorithm is that it has needless computation. This means that it spends a long time for the bees algorithm converge the optimum solution. In this study, the parallel bees algorithm technique is proposed for overcoming of this issue. Due to that, this would lead to reduce the required time to get a solution with faster results accuracy than original Bees Algorithm. 2012 Thesis https://etd.uum.edu.my/2924/ https://etd.uum.edu.my/2924/1/Nayif_Mohammed_Hammash.pdf text eng validuser https://etd.uum.edu.my/2924/4/Nayif_Mohammed_Hammash.pdf text eng public masters masters Universiti Utara Malaysia Özbakir, L., Baykasoglu, A., & Tapkan, P. I. (2010). Bees algorithm for generalized assignment problem. Applied Mathematics and Computation, 215(11), 3782-3795. Abraham, A., & Jain, L. (2005). Evolutionary multiobjective optimization. Evolutionary Multiobjective Optimization, 1-6. Agarwal, A., & Kubiatowicz, J. D. (1998). 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