Adaptation of Population Size in Differential Evolution and Its Effects on Localization of Target Nodes
The differential evolution (DE) is a well known population-based evolutionary algorithm that has shown capabilities for solving real-world problems such as resource allocation, multicast routing, and localization of target nodes. However, the accuracy of the DE, like other evolutionary algorithms, d...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9913992/ |
| _version_ | 1811182581767471104 |
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| author | Lismer Andres Caceres Najarro Iickho Song Kiseon Kim |
| author_facet | Lismer Andres Caceres Najarro Iickho Song Kiseon Kim |
| author_sort | Lismer Andres Caceres Najarro |
| collection | DOAJ |
| description | The differential evolution (DE) is a well known population-based evolutionary algorithm that has shown capabilities for solving real-world problems such as resource allocation, multicast routing, and localization of target nodes. However, the accuracy of the DE, like other evolutionary algorithms, depends on the settings of its control parameters. The localization of target nodes is highly nonlinear and multi-modal, which may trap the DE in a local optimum. A local optimum may be avoided by a proper selection of the control parameters. One of the key control parameters is the population size (PS), which affects directly the localization accuracy and computational complexity. Finding an adequate PS throughout the evolution process is a challenging task. Even if an adequate PS is found it may not be the adequate PS anymore when the scenario of a problem changes. Although several approaches have been proposed for adapting the PS, they have not been evaluated when solving the localization problem. In this paper, a comprehensive comparison in terms of accuracy and computational demand is conducted among the state-of-the-art PS adaptation techniques when employed with the DE for solving the localization problem of target nodes in various scenarios. We also propose three new PS adaptation techniques, namely, exponential, parabolic, and logistic reduction. The results from extensive numerical simulations show that, after setting the initial PS properly, there is no technique that outperforms the others in practically all the scenario of the localization problem. Additionally, the DE with the proposed techniques provides competitive localization accuracy with considerably less computational complexity. Specifically, The proposed approaches reduce the computational demand by approximately 50 % over the standard DE in all the scenarios considered here. |
| first_indexed | 2024-04-11T09:34:13Z |
| format | Article |
| id | doaj.art-2f80b65bc9fb4c0f94fbdcbdb097c53d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T09:34:13Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2f80b65bc9fb4c0f94fbdcbdb097c53d2022-12-22T04:31:46ZengIEEEIEEE Access2169-35362022-01-011010778510779810.1109/ACCESS.2022.32130609913992Adaptation of Population Size in Differential Evolution and Its Effects on Localization of Target NodesLismer Andres Caceres Najarro0https://orcid.org/0000-0002-2784-0953Iickho Song1https://orcid.org/0000-0002-6874-1556Kiseon Kim2https://orcid.org/0000-0001-9166-0570School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, Republic of KoreaSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of KoreaSchool of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, Republic of KoreaThe differential evolution (DE) is a well known population-based evolutionary algorithm that has shown capabilities for solving real-world problems such as resource allocation, multicast routing, and localization of target nodes. However, the accuracy of the DE, like other evolutionary algorithms, depends on the settings of its control parameters. The localization of target nodes is highly nonlinear and multi-modal, which may trap the DE in a local optimum. A local optimum may be avoided by a proper selection of the control parameters. One of the key control parameters is the population size (PS), which affects directly the localization accuracy and computational complexity. Finding an adequate PS throughout the evolution process is a challenging task. Even if an adequate PS is found it may not be the adequate PS anymore when the scenario of a problem changes. Although several approaches have been proposed for adapting the PS, they have not been evaluated when solving the localization problem. In this paper, a comprehensive comparison in terms of accuracy and computational demand is conducted among the state-of-the-art PS adaptation techniques when employed with the DE for solving the localization problem of target nodes in various scenarios. We also propose three new PS adaptation techniques, namely, exponential, parabolic, and logistic reduction. The results from extensive numerical simulations show that, after setting the initial PS properly, there is no technique that outperforms the others in practically all the scenario of the localization problem. Additionally, the DE with the proposed techniques provides competitive localization accuracy with considerably less computational complexity. Specifically, The proposed approaches reduce the computational demand by approximately 50 % over the standard DE in all the scenarios considered here.https://ieeexplore.ieee.org/document/9913992/Differential evolutionevolutionary algorithmslocalizationpopulation size controlwireless sensor networks |
| spellingShingle | Lismer Andres Caceres Najarro Iickho Song Kiseon Kim Adaptation of Population Size in Differential Evolution and Its Effects on Localization of Target Nodes IEEE Access Differential evolution evolutionary algorithms localization population size control wireless sensor networks |
| title | Adaptation of Population Size in Differential Evolution and Its Effects on Localization of Target Nodes |
| title_full | Adaptation of Population Size in Differential Evolution and Its Effects on Localization of Target Nodes |
| title_fullStr | Adaptation of Population Size in Differential Evolution and Its Effects on Localization of Target Nodes |
| title_full_unstemmed | Adaptation of Population Size in Differential Evolution and Its Effects on Localization of Target Nodes |
| title_short | Adaptation of Population Size in Differential Evolution and Its Effects on Localization of Target Nodes |
| title_sort | adaptation of population size in differential evolution and its effects on localization of target nodes |
| topic | Differential evolution evolutionary algorithms localization population size control wireless sensor networks |
| url | https://ieeexplore.ieee.org/document/9913992/ |
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