Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method
Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector. Various app...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Published: |
College of Science for Women/ University of Baghdad
2021
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/93481/ |
| _version_ | 1848861856424263680 |
|---|---|
| author | Mohammed, Rawia Tahrir Yaakob, Razali Mohd Sharef, Nurfadhlina Abdullah, Rusli |
| author_facet | Mohammed, Rawia Tahrir Yaakob, Razali Mohd Sharef, Nurfadhlina Abdullah, Rusli |
| author_sort | Mohammed, Rawia Tahrir |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector. Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art algorithms perform using one or two performance indicators without clear evidence or justification of the efficiency of these indicators over others. Thus, unify a set of most suitable evaluation criteria of the MaOO is needed. This study proposed a distinct unifying model for the MaOO evaluation criteria using the fuzzy Delphi method. The study followed a systematic procedure to analyze 49 evaluation criteria, sub-criteria, and its performance indicators, a penal of 23 domain experts, participated in this study. Lastly, the most suitable criteria outcomes are formulated in the unifying model and evaluate by experts to verify the appropriateness and suitability of the model in assessing the MaOO algorithms fairly and effectively. |
| first_indexed | 2025-11-15T13:07:47Z |
| format | Article |
| id | upm-93481 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T13:07:47Z |
| publishDate | 2021 |
| publisher | College of Science for Women/ University of Baghdad |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-934812023-01-13T03:27:43Z http://psasir.upm.edu.my/id/eprint/93481/ Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method Mohammed, Rawia Tahrir Yaakob, Razali Mohd Sharef, Nurfadhlina Abdullah, Rusli Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector. Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art algorithms perform using one or two performance indicators without clear evidence or justification of the efficiency of these indicators over others. Thus, unify a set of most suitable evaluation criteria of the MaOO is needed. This study proposed a distinct unifying model for the MaOO evaluation criteria using the fuzzy Delphi method. The study followed a systematic procedure to analyze 49 evaluation criteria, sub-criteria, and its performance indicators, a penal of 23 domain experts, participated in this study. Lastly, the most suitable criteria outcomes are formulated in the unifying model and evaluate by experts to verify the appropriateness and suitability of the model in assessing the MaOO algorithms fairly and effectively. College of Science for Women/ University of Baghdad 2021-12-20 Article PeerReviewed Mohammed, Rawia Tahrir and Yaakob, Razali and Mohd Sharef, Nurfadhlina and Abdullah, Rusli (2021) Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method. Baghdad Science Journal, 18 (suppl.4). 1423 - 1430. ISSN 2078-8665; ESSN: 2411-7986 https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6649 10.21123/bsj.2021.18.4(Suppl.).1423 |
| spellingShingle | Mohammed, Rawia Tahrir Yaakob, Razali Mohd Sharef, Nurfadhlina Abdullah, Rusli Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method |
| title | Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method |
| title_full | Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method |
| title_fullStr | Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method |
| title_full_unstemmed | Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method |
| title_short | Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method |
| title_sort | unifying the evaluation criteria of many objectives optimization using fuzzy delphi method |
| url | http://psasir.upm.edu.my/id/eprint/93481/ http://psasir.upm.edu.my/id/eprint/93481/ http://psasir.upm.edu.my/id/eprint/93481/ |