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Software module clustering based on the fuzzy adaptive teaching learning based optimization algorithm
Universiti Malaysia Pahang, MYS.
Universiti Malaysia Pahang, MYS; University of Malakand, PAK.
Universiti Teknologi MARA Pahang, MYS.
2019 (English)In: Lecture Notes in Networks and Systems, Springer , 2019, p. 167-177Conference paper, Published paper (Refereed)
Abstract [en]

Although showing competitive performances in many real-world optimization problems, Teaching Learning based Optimization Algorithm (TLBO) has been criticized for having poor control on exploration and exploitation. Addressing these issues, a new variant of TLBO called Adaptive Fuzzy Teaching Learning based Optimization (ATLBO) has been developed in the literature. This paper describes the adoption of Fuzzy Adaptive Fuzzy Teaching Learning based Optimization (ATLBO) for software module clustering problem. Comparative studies with the original Teaching Learning based Optimization (TLBO) and other Fuzzy TLBO variant demonstrate that ATLBO gives superior performance owing to its adaptive selection of search operators based on the need of the current search. © Springer Nature Singapore Pte Ltd. 2019.

Place, publisher, year, edition, pages
Springer , 2019. p. 167-177
Series
Lecture Notes in Networks and Systems, ISSN 2367-3370
Keywords [en]
Adaptive teaching learning based optimization, Mamdani fuzzy, Search-based software engineering, Software module clustering
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-86826DOI: 10.1007/978-981-13-6031-2_3Scopus ID: 2-s2.0-85066131390OAI: oai:DiVA.org:kau-86826DiVA, id: diva2:1608275
Conference
Lecture Notes in Networks and Systems
Available from: 2021-11-03 Created: 2021-11-03 Last updated: 2021-11-25Bibliographically approved

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Ahmed, Bestoun S.

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CiteExportLink to record
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Language
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  • nn-NB
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  • Other locale
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Output format
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