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 ap...

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Main Authors: Rawia Tahrir Mohammed, Razali Yaakob, Nurfadhlina Mohd Sharef, Rusli Abdullah
Format: Article
Language:English
Published: University of Baghdad, College of Science for Women 2021-12-01
Series:مجلة بغداد للعلوم
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Online Access:https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6649
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author Rawia Tahrir Mohammed
Razali Yaakob
Nurfadhlina Mohd Sharef
Rusli Abdullah
author_facet Rawia Tahrir Mohammed
Razali Yaakob
Nurfadhlina Mohd Sharef
Rusli Abdullah
author_sort Rawia Tahrir Mohammed
collection DOAJ
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.
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publishDate 2021-12-01
publisher University of Baghdad, College of Science for Women
record_format Article
series مجلة بغداد للعلوم
spelling doaj-art-78fb249fee4b45599934b37bcef53b2c2025-08-20T03:33:50ZengUniversity of Baghdad, College of Science for Womenمجلة بغداد للعلوم2078-86652411-79862021-12-01184(Suppl.)10.21123/bsj.2021.18.4(Suppl.).1423Unifying The Evaluation Criteria Of Many Objectives Optimization Using Fuzzy Delphi MethodRawia Tahrir Mohammed0Razali Yaakob1Nurfadhlina Mohd Sharef2Rusli Abdullah3Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Selangor, Malaysia & Geomatika University College, Kuala Lumpur, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Selangor, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Selangor, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Selangor, MalaysiaMany 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.https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6649Evaluation Criteria, Fuzzy Delphi, Many Objectives Optimization, Unifying Model
spellingShingle Rawia Tahrir Mohammed
Razali Yaakob
Nurfadhlina Mohd Sharef
Rusli Abdullah
Unifying The Evaluation Criteria Of Many Objectives Optimization Using Fuzzy Delphi Method
مجلة بغداد للعلوم
Evaluation Criteria, Fuzzy Delphi, Many Objectives Optimization, Unifying Model
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
topic Evaluation Criteria, Fuzzy Delphi, Many Objectives Optimization, Unifying Model
url https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6649
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AT razaliyaakob unifyingtheevaluationcriteriaofmanyobjectivesoptimizationusingfuzzydelphimethod
AT nurfadhlinamohdsharef unifyingtheevaluationcriteriaofmanyobjectivesoptimizationusingfuzzydelphimethod
AT rusliabdullah unifyingtheevaluationcriteriaofmanyobjectivesoptimizationusingfuzzydelphimethod