New modified controlled bat algorithm for numerical optimization problem
Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. BA leverages the echolocation feature of bats produced by imitating the bats’ searching behavior. BA faces premature convergence due to its local search capability. In...
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Tech Science Press
2022
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my.ums.eprints.318482022-03-15T03:36:54Z https://eprints.ums.edu.my/id/eprint/31848/ New modified controlled bat algorithm for numerical optimization problem Waqas Haider Bangyal Abdul Hameed Jamil Ahmad Kashif Nisar Muhammad Reazul Haque Ag. Asri Ag. Ibrahim Joel J. P. C. Rodrigues M. Adil Khan Danda B. Rawat Richard Etengu QA75.5-76.95 Electronic computers. Computer science Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. BA leverages the echolocation feature of bats produced by imitating the bats’ searching behavior. BA faces premature convergence due to its local search capability. Instead of using the standard uniform walk, the Torus walk is viewed as a promising alternative to improve the local search capability. In this work, we proposed an improved variation of BA by applying torus walk to improve diversity and convergence. The proposed. Modern Computerized Bat Algorithm (MCBA) approach has been examined for fifteen well-known benchmark test problems. The finding of our technique shows promising performance as compared to the standard PSO and standard BA. The proposed MCBA, BPA, Standard PSO, and Standard BA have been examined for well-known benchmark test problems and training of the artificial neural network (ANN). We have performed experiments using eight benchmark datasets applied from the worldwide famous machine-learning (ML) repository of UCI. Simulation results have shown that the training of an ANN with MCBA-NN algorithm tops the list considering exactness, with more superiority compared to the traditional methodologies. The MCBA-NN algorithm may be used effectively for data classification and statistical problems in the future. Tech Science Press 2022 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/31848/1/Bat%20algorithm%20%28BA%29%20is%20an%20eminent%20meta-heuristic%20algorithm%20that%20has%20been%20widely%20used%20to%20solve%20diverse%20kinds%20of%20optimization%20problems.pdf text en https://eprints.ums.edu.my/id/eprint/31848/2/Bat%20algorithm%20%28BA%29%20is%20an%20eminent%20meta-heuristic%20algorithm%20that%20has%20been%20widely%20used%20to%20solve%20diverse%20kinds%20of%20optimization%20problems1.pdf Waqas Haider Bangyal and Abdul Hameed and Jamil Ahmad and Kashif Nisar and Muhammad Reazul Haque and Ag. Asri Ag. Ibrahim and Joel J. P. C. Rodrigues and M. Adil Khan and Danda B. Rawat and Richard Etengu (2022) New modified controlled bat algorithm for numerical optimization problem. Computers, Materials & Continua, 70 (2). pp. 2241-2259. ISSN 1546-2226 https://www.techscience.com/ueditor/files/cmc/TSP_CMC_70-2/TSP_CMC_17789/TSP_CMC_17789.pdf http://dx.doi.org/10.32604/cmc.2022.017789 |
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QA75.5-76.95 Electronic computers. Computer science Waqas Haider Bangyal Abdul Hameed Jamil Ahmad Kashif Nisar Muhammad Reazul Haque Ag. Asri Ag. Ibrahim Joel J. P. C. Rodrigues M. Adil Khan Danda B. Rawat Richard Etengu New modified controlled bat algorithm for numerical optimization problem |
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Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. BA leverages the echolocation feature of bats produced by imitating the bats’ searching behavior. BA faces premature convergence due to its local search capability. Instead of using the standard uniform walk, the Torus walk is viewed as a promising alternative to improve the local search capability. In this work, we proposed an improved variation of BA by applying torus walk to improve diversity and convergence. The proposed. Modern Computerized Bat Algorithm (MCBA) approach has been examined for fifteen well-known benchmark test problems. The finding of our technique shows promising performance as compared to the standard PSO and standard BA. The proposed MCBA, BPA, Standard PSO, and Standard BA have been examined for well-known benchmark test problems and training of the artificial neural network (ANN). We have performed experiments using eight benchmark datasets applied from the worldwide famous machine-learning (ML) repository of UCI. Simulation results have shown that the training of an ANN with MCBA-NN algorithm tops the list considering exactness, with more superiority compared to the traditional methodologies. The MCBA-NN algorithm may be used effectively for data classification and statistical problems in the future. |
format |
Article |
author |
Waqas Haider Bangyal Abdul Hameed Jamil Ahmad Kashif Nisar Muhammad Reazul Haque Ag. Asri Ag. Ibrahim Joel J. P. C. Rodrigues M. Adil Khan Danda B. Rawat Richard Etengu |
author_facet |
Waqas Haider Bangyal Abdul Hameed Jamil Ahmad Kashif Nisar Muhammad Reazul Haque Ag. Asri Ag. Ibrahim Joel J. P. C. Rodrigues M. Adil Khan Danda B. Rawat Richard Etengu |
author_sort |
Waqas Haider Bangyal |
title |
New modified controlled bat algorithm for numerical optimization problem |
title_short |
New modified controlled bat algorithm for numerical optimization problem |
title_full |
New modified controlled bat algorithm for numerical optimization problem |
title_fullStr |
New modified controlled bat algorithm for numerical optimization problem |
title_full_unstemmed |
New modified controlled bat algorithm for numerical optimization problem |
title_sort |
new modified controlled bat algorithm for numerical optimization problem |
publisher |
Tech Science Press |
publishDate |
2022 |
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https://eprints.ums.edu.my/id/eprint/31848/1/Bat%20algorithm%20%28BA%29%20is%20an%20eminent%20meta-heuristic%20algorithm%20that%20has%20been%20widely%20used%20to%20solve%20diverse%20kinds%20of%20optimization%20problems.pdf https://eprints.ums.edu.my/id/eprint/31848/2/Bat%20algorithm%20%28BA%29%20is%20an%20eminent%20meta-heuristic%20algorithm%20that%20has%20been%20widely%20used%20to%20solve%20diverse%20kinds%20of%20optimization%20problems1.pdf https://eprints.ums.edu.my/id/eprint/31848/ https://www.techscience.com/ueditor/files/cmc/TSP_CMC_70-2/TSP_CMC_17789/TSP_CMC_17789.pdf http://dx.doi.org/10.32604/cmc.2022.017789 |
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13.18916 |