Deriving priority in AHP using Evolutionary Computing approach

In the real world, human will face the problem and dilemma to making decision. Making decision is the critical part in choosing the best solution. Multi-criteria decision making (MCDM) is one of the most well known branches of decision making and it is referring to making decision in the presence of...

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Main Authors: Zakaria, Nur Farha, Mohamed Dahlan, Halina, Che Hussin, Ab. Razak
Format: Article
Published: 2010
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Online Access:http://eprints.utm.my/id/eprint/25091/
https://www.researchgate.net/publication/287450075_Deriving_priority_in_AHP_using_Evolutionary_Computing_approach
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spelling my.utm.250912018-03-27T05:52:58Z http://eprints.utm.my/id/eprint/25091/ Deriving priority in AHP using Evolutionary Computing approach Zakaria, Nur Farha Mohamed Dahlan, Halina Che Hussin, Ab. Razak QA75 Electronic computers. Computer science In the real world, human will face the problem and dilemma to making decision. Making decision is the critical part in choosing the best solution. Multi-criteria decision making (MCDM) is one of the most well known branches of decision making and it is referring to making decision in the presence of multiple criteria. MCDM problem are common occurrences in everyday life. In 1977, Saaty introduced Analytic Hierarchy Process (AHP) to solve the MCDM problem. The AHP is widely used for MCDM. Since AHP has been introduced, it has been applied in numerous situations with impressive results. However, AHP has been also criticized in the literature review, mainly in priority derivation procedure. This paper has identified three main problems in current priority derivation procedure which are: (1) Inconsistency of the judgment, (2) Non-evolutionary computing approach, and (3) Accuracy performance of the prioritization method. To solve the criticism and the problems; this paper proposes AHPEC which is using Evolutionary Computing (EC) to derive priorities in AHP. The AHPEC gives better result compare to the other prioritization methods based on accuracy of derived priorities. The comparison is based on the value of Total Deviation (TD) which is measure accuracy o the solution. The case study from Srdjevic, 2005 was chosen to compare the performance of the AHPEC and the current prioritization methods based on accuracy of the solution as a criterion to be optimized. 2010 Article PeerReviewed Zakaria, Nur Farha and Mohamed Dahlan, Halina and Che Hussin, Ab. Razak (2010) Deriving priority in AHP using Evolutionary Computing approach. Wseas Transactions on information Science and Applications, 7 (5). 714 - 724. ISSN 1790-0832 https://www.researchgate.net/publication/287450075_Deriving_priority_in_AHP_using_Evolutionary_Computing_approach
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Zakaria, Nur Farha
Mohamed Dahlan, Halina
Che Hussin, Ab. Razak
Deriving priority in AHP using Evolutionary Computing approach
description In the real world, human will face the problem and dilemma to making decision. Making decision is the critical part in choosing the best solution. Multi-criteria decision making (MCDM) is one of the most well known branches of decision making and it is referring to making decision in the presence of multiple criteria. MCDM problem are common occurrences in everyday life. In 1977, Saaty introduced Analytic Hierarchy Process (AHP) to solve the MCDM problem. The AHP is widely used for MCDM. Since AHP has been introduced, it has been applied in numerous situations with impressive results. However, AHP has been also criticized in the literature review, mainly in priority derivation procedure. This paper has identified three main problems in current priority derivation procedure which are: (1) Inconsistency of the judgment, (2) Non-evolutionary computing approach, and (3) Accuracy performance of the prioritization method. To solve the criticism and the problems; this paper proposes AHPEC which is using Evolutionary Computing (EC) to derive priorities in AHP. The AHPEC gives better result compare to the other prioritization methods based on accuracy of derived priorities. The comparison is based on the value of Total Deviation (TD) which is measure accuracy o the solution. The case study from Srdjevic, 2005 was chosen to compare the performance of the AHPEC and the current prioritization methods based on accuracy of the solution as a criterion to be optimized.
format Article
author Zakaria, Nur Farha
Mohamed Dahlan, Halina
Che Hussin, Ab. Razak
author_facet Zakaria, Nur Farha
Mohamed Dahlan, Halina
Che Hussin, Ab. Razak
author_sort Zakaria, Nur Farha
title Deriving priority in AHP using Evolutionary Computing approach
title_short Deriving priority in AHP using Evolutionary Computing approach
title_full Deriving priority in AHP using Evolutionary Computing approach
title_fullStr Deriving priority in AHP using Evolutionary Computing approach
title_full_unstemmed Deriving priority in AHP using Evolutionary Computing approach
title_sort deriving priority in ahp using evolutionary computing approach
publishDate 2010
url http://eprints.utm.my/id/eprint/25091/
https://www.researchgate.net/publication/287450075_Deriving_priority_in_AHP_using_Evolutionary_Computing_approach
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score 13.209306