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            <name>Title</name>
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                <text>Conference Papers</text>
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    <name>Conference Paper</name>
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          <name>Title</name>
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              <text>Calibration of Optimal Trigonometric Probability for Asynchronous Differential Evolution</text>
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          <name>Subject</name>
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              <text>Asynchronous differential evolution; Evolutionary algorithms; Optimization; Trigonometric mutation</text>
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              <text>Parallel optimization and strong exploration are the main features of asynchronous differential evolution (ADE). The population is updated instantly in ADE by replacing the target vector if a better vector is found during the selection operation. This feature of ADE makes it different from differential evolution (DE). With this feature, ADE works asynchronously. In this work, ADE and trigonometric mutation are embedded together to raise the performance of an algorithm. The work finds out the best trigonometric probability value for asynchronous differential evolution. Two values of trigonometric mutation probability (PTMO) are tested to obtain the optimum setting of PTMO. The work presented in this paper is tested over a number of benchmark functions. The benchmark functions results are compared for two values of PTMO and discussed in detail. The proposed work outperforms the competitive algorithms. A nonparametric statistical analysis is also performed to validate the results.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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          <name>Creator</name>
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            <elementText elementTextId="173477">
              <text>Yadav V.; Yadav A.K.; Sharma S.; Kumar S.</text>
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          <name>Source</name>
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              <text>Lecture Notes in Networks and Systems, Vol-698, pp. 807-818.</text>
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          <name>Publisher</name>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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          <name>Date</name>
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              <text>2023-01-01</text>
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          <name>Identifier</name>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-99-3250-4_61" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-99-3250-4_61&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172173095&amp;amp;doi=10.1007%2F978-981-99-3250-4_61&amp;amp;partnerID=40&amp;amp;md5=eed9b6556762cf8e237f5978729e4fea" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172173095&amp;amp;doi=10.1007%2f978-981-99-3250-4_61&amp;amp;partnerID=40&amp;amp;md5=eed9b6556762cf8e237f5978729e4fea&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 23673370; ISBN: 978-981993249-8</text>
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          <name>Format</name>
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              <text>Online</text>
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              <text>English</text>
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              <text>Yadav V., Manipal University Jaipur, Rajasthan, Jaipur, India; Yadav A.K., ASET, Amity University Rajasthan, Rajasthan, Jaipur, India; Sharma S., Manipal University Jaipur, Rajasthan, Jaipur, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India</text>
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