A Modified Bat Algorithm with Conjugate Gradient Method for Global Optimization
Metaheuristic algorithms are used to solve many optimization problems. Firefly algorithm, particle swarm improvement, harmonic search, and bat algorithm are used as search algorithms to find the optimal solution to the problem field. In this paper, we have investigated and analyzed a new scaled conj...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | International Journal of Mathematics and Mathematical Sciences |
| Online Access: | http://dx.doi.org/10.1155/2020/4795793 |
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| author | Huda I. Ahmed Eman T. Hamed Hamsa Th. Saeed Chilmeran |
| author_facet | Huda I. Ahmed Eman T. Hamed Hamsa Th. Saeed Chilmeran |
| author_sort | Huda I. Ahmed |
| collection | DOAJ |
| description | Metaheuristic algorithms are used to solve many optimization problems. Firefly algorithm, particle swarm improvement, harmonic search, and bat algorithm are used as search algorithms to find the optimal solution to the problem field. In this paper, we have investigated and analyzed a new scaled conjugate gradient algorithm and its implementation, based on the exact Wolfe line search conditions and the restart Powell criterion. The new spectral conjugate gradient algorithm is a modification of the Birgin and Martínez method, a manner to overcome the lack of positive definiteness of the matrix defining the search direction. The preliminary computational results for a set of 30 unconstrained optimization test problems show that this new spectral conjugate gradient outperforms a standard conjugate gradient in this field and we have applied the newly proposed spectral conjugate gradient algorithm in bat algorithm to reach the lowest possible goal of bat algorithm. The newly proposed approach, namely, the directional bat algorithm (CG-BAT), has been then tested using several standard and nonstandard benchmarks from the CEC’2005 benchmark suite with five other algorithms and has been then tested using nonparametric statistical tests and the statistical test results show the superiority of the directional bat algorithm, and also we have adopted the performance profiles given by Dolan and More which show the superiority of the new algorithm (CG-BAT). |
| format | Article |
| id | doaj-art-bc911051e5634bf682d5d50f33581290 |
| institution | Kabale University |
| issn | 0161-1712 1687-0425 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Mathematics and Mathematical Sciences |
| spelling | doaj-art-bc911051e5634bf682d5d50f335812902025-02-03T01:04:06ZengWileyInternational Journal of Mathematics and Mathematical Sciences0161-17121687-04252020-01-01202010.1155/2020/47957934795793A Modified Bat Algorithm with Conjugate Gradient Method for Global OptimizationHuda I. Ahmed0Eman T. Hamed1Hamsa Th. Saeed Chilmeran2Department of Operation Researches and Intelligent Techniques, College of Computers Sciences and Mathematics, University of Mosul, Mosul, IraqDepartment of Operation Researches and Intelligent Techniques, College of Computers Sciences and Mathematics, University of Mosul, Mosul, IraqDepartment of Mathematics, College of Computers Sciences and Mathematics, University of Mosul, Mosul, IraqMetaheuristic algorithms are used to solve many optimization problems. Firefly algorithm, particle swarm improvement, harmonic search, and bat algorithm are used as search algorithms to find the optimal solution to the problem field. In this paper, we have investigated and analyzed a new scaled conjugate gradient algorithm and its implementation, based on the exact Wolfe line search conditions and the restart Powell criterion. The new spectral conjugate gradient algorithm is a modification of the Birgin and Martínez method, a manner to overcome the lack of positive definiteness of the matrix defining the search direction. The preliminary computational results for a set of 30 unconstrained optimization test problems show that this new spectral conjugate gradient outperforms a standard conjugate gradient in this field and we have applied the newly proposed spectral conjugate gradient algorithm in bat algorithm to reach the lowest possible goal of bat algorithm. The newly proposed approach, namely, the directional bat algorithm (CG-BAT), has been then tested using several standard and nonstandard benchmarks from the CEC’2005 benchmark suite with five other algorithms and has been then tested using nonparametric statistical tests and the statistical test results show the superiority of the directional bat algorithm, and also we have adopted the performance profiles given by Dolan and More which show the superiority of the new algorithm (CG-BAT).http://dx.doi.org/10.1155/2020/4795793 |
| spellingShingle | Huda I. Ahmed Eman T. Hamed Hamsa Th. Saeed Chilmeran A Modified Bat Algorithm with Conjugate Gradient Method for Global Optimization International Journal of Mathematics and Mathematical Sciences |
| title | A Modified Bat Algorithm with Conjugate Gradient Method for Global Optimization |
| title_full | A Modified Bat Algorithm with Conjugate Gradient Method for Global Optimization |
| title_fullStr | A Modified Bat Algorithm with Conjugate Gradient Method for Global Optimization |
| title_full_unstemmed | A Modified Bat Algorithm with Conjugate Gradient Method for Global Optimization |
| title_short | A Modified Bat Algorithm with Conjugate Gradient Method for Global Optimization |
| title_sort | modified bat algorithm with conjugate gradient method for global optimization |
| url | http://dx.doi.org/10.1155/2020/4795793 |
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