Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites

Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites

The teaching learning-based optimization (TLBO) algorithm has shown competitive performance in solving numerous real-world optimization problems. Nevertheless, this algorithm requires better control for exploitation and exploration to prevent premature convergence (i.e., trapped in local optima), as...

Full description

Bibliographic Details
Main Authors: Kamal Z., Zamli, Fakhrud, Din, Salmi, Baharom, Ahmed, Bestoun S.
Format: Article
Language:English
Published: Elsevier Ltd 2017
Subjects:
QA76 Computer software
Online Access:http://umpir.ump.edu.my/id/eprint/16453/
http://umpir.ump.edu.my/id/eprint/16453/
http://umpir.ump.edu.my/id/eprint/16453/
http://umpir.ump.edu.my/id/eprint/16453/1/fskkp-2017-kamal-Fuzzy%20adaptive%20teaching%20learning-based1.pdf
id ump-16453
recordtype eprints
spelling ump-164532018-01-16T00:48:26Z http://umpir.ump.edu.my/id/eprint/16453/ Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites Kamal Z., Zamli Fakhrud, Din Salmi, Baharom Ahmed, Bestoun S. QA76 Computer software The teaching learning-based optimization (TLBO) algorithm has shown competitive performance in solving numerous real-world optimization problems. Nevertheless, this algorithm requires better control for exploitation and exploration to prevent premature convergence (i.e., trapped in local optima), as well as enhance solution diversity. Thus, this paper proposes a new TLBO variant based on Mamdani fuzzy inference system, called ATLBO, to permit adaptive selection of its global and local search operations. In order to assess its performances, we adopt ATLBO for the mixed strength t-way test generation problem. Experimental results reveal that ATLBO exhibits competitive performances against the original TLBO and other meta-heuristic counterparts. Elsevier Ltd 2017 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/16453/1/fskkp-2017-kamal-Fuzzy%20adaptive%20teaching%20learning-based1.pdf Kamal Z., Zamli and Fakhrud, Din and Salmi, Baharom and Ahmed, Bestoun S. (2017) Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites. Engineering Applications of Artificial Intelligence, 59. pp. 35-50. ISSN 0952-1976 https://doi.org/10.1016/j.engappai.2016.12.014 DOI: 10.1016/j.engappai.2016.12.014
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Kamal Z., Zamli
Fakhrud, Din
Salmi, Baharom
Ahmed, Bestoun S.
Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites
description The teaching learning-based optimization (TLBO) algorithm has shown competitive performance in solving numerous real-world optimization problems. Nevertheless, this algorithm requires better control for exploitation and exploration to prevent premature convergence (i.e., trapped in local optima), as well as enhance solution diversity. Thus, this paper proposes a new TLBO variant based on Mamdani fuzzy inference system, called ATLBO, to permit adaptive selection of its global and local search operations. In order to assess its performances, we adopt ATLBO for the mixed strength t-way test generation problem. Experimental results reveal that ATLBO exhibits competitive performances against the original TLBO and other meta-heuristic counterparts.
format Article
author Kamal Z., Zamli
Fakhrud, Din
Salmi, Baharom
Ahmed, Bestoun S.
author_facet Kamal Z., Zamli
Fakhrud, Din
Salmi, Baharom
Ahmed, Bestoun S.
author_sort Kamal Z., Zamli
title Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites
title_short Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites
title_full Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites
title_fullStr Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites
title_full_unstemmed Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites
title_sort fuzzy adaptive teaching learning-based optimization strategy for the problem of generating mixed strength t-way test suites
publisher Elsevier Ltd
publishDate 2017
url http://umpir.ump.edu.my/id/eprint/16453/
http://umpir.ump.edu.my/id/eprint/16453/
http://umpir.ump.edu.my/id/eprint/16453/
http://umpir.ump.edu.my/id/eprint/16453/1/fskkp-2017-kamal-Fuzzy%20adaptive%20teaching%20learning-based1.pdf
first_indexed 2023-09-18T22:22:09Z
last_indexed 2023-09-18T22:22:09Z
_version_ 1777415727637069824

Similar Items