Ringed Seal Search for Global Optimization via a Sensitive Search Model.
The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed...
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ftahmaddahlanuni:oai:eprints.uad.ac.id:11647 2024-09-15T18:32:23+00:00 Ringed Seal Search for Global Optimization via a Sensitive Search Model. Saadi, Younes Herawan, Tutut Balakrishnan, Vimala Risnumawan, Anhar Tri Riyadi Yanto, Iwan Chiroma, Haruna 2018-11-06 text http://eprints.uad.ac.id/11647/ http://eprints.uad.ac.id/11647/1/Ringed%20Seal%20Search%20for%20Global%20Optimization%20via%20a%20Sensitive%20Search%20Model.pdf en eng https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0144371 http://eprints.uad.ac.id/11647/1/Ringed%20Seal%20Search%20for%20Global%20Optimization%20via%20a%20Sensitive%20Search%20Model.pdf Saadi, Younes and Herawan, Tutut and Balakrishnan, Vimala and Risnumawan, Anhar and Tri Riyadi Yanto, Iwan and Chiroma, Haruna (2018) Ringed Seal Search for Global Optimization via a Sensitive Search Model. [Artikel Dosen] QA75 Electronic computers. Computer science Artikel Dosen PeerReviewed 2018 ftahmaddahlanuni 2024-06-27T04:20:08Z The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behav-ior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emit-ted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and valida-tions were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of conver-gence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global optimization problems. Course Material ringed seal Universitas Ahmad Dahlan Yogyakarta: Eprints UAD |
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Universitas Ahmad Dahlan Yogyakarta: Eprints UAD |
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English |
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QA75 Electronic computers. Computer science |
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QA75 Electronic computers. Computer science Saadi, Younes Herawan, Tutut Balakrishnan, Vimala Risnumawan, Anhar Tri Riyadi Yanto, Iwan Chiroma, Haruna Ringed Seal Search for Global Optimization via a Sensitive Search Model. |
topic_facet |
QA75 Electronic computers. Computer science |
description |
The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behav-ior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emit-ted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and valida-tions were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of conver-gence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global optimization problems. |
format |
Course Material |
author |
Saadi, Younes Herawan, Tutut Balakrishnan, Vimala Risnumawan, Anhar Tri Riyadi Yanto, Iwan Chiroma, Haruna |
author_facet |
Saadi, Younes Herawan, Tutut Balakrishnan, Vimala Risnumawan, Anhar Tri Riyadi Yanto, Iwan Chiroma, Haruna |
author_sort |
Saadi, Younes |
title |
Ringed Seal Search for Global Optimization via a Sensitive Search Model. |
title_short |
Ringed Seal Search for Global Optimization via a Sensitive Search Model. |
title_full |
Ringed Seal Search for Global Optimization via a Sensitive Search Model. |
title_fullStr |
Ringed Seal Search for Global Optimization via a Sensitive Search Model. |
title_full_unstemmed |
Ringed Seal Search for Global Optimization via a Sensitive Search Model. |
title_sort |
ringed seal search for global optimization via a sensitive search model. |
publisher |
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0144371 |
publishDate |
2018 |
url |
http://eprints.uad.ac.id/11647/ http://eprints.uad.ac.id/11647/1/Ringed%20Seal%20Search%20for%20Global%20Optimization%20via%20a%20Sensitive%20Search%20Model.pdf |
genre |
ringed seal |
genre_facet |
ringed seal |
op_relation |
http://eprints.uad.ac.id/11647/1/Ringed%20Seal%20Search%20for%20Global%20Optimization%20via%20a%20Sensitive%20Search%20Model.pdf Saadi, Younes and Herawan, Tutut and Balakrishnan, Vimala and Risnumawan, Anhar and Tri Riyadi Yanto, Iwan and Chiroma, Haruna (2018) Ringed Seal Search for Global Optimization via a Sensitive Search Model. [Artikel Dosen] |
_version_ |
1810474113342373888 |