Towards Group Fuzzy Analytical Hierarchy Process

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dc.contributor.author Musumba, George Wamamu
dc.contributor.author Wario, Ruth Diko
dc.date.accessioned 2018-12-18T08:37:40Z
dc.date.available 2018-12-18T08:37:40Z
dc.date.issued 2018-07-05
dc.identifier.citation Musumba G.W., Wario R.D. (2018) Towards Group Fuzzy Analytical Hierarchy Process. In: Mekuria F., Nigussie E., Dargie W., Edward M., Tegegne T. (eds) Information and Communication Technology for Development for Africa. ICT4DA 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 244. Springer, Cham en_US
dc.identifier.uri http://41.89.227.156:8080/xmlui/handle/123456789/797
dc.description.abstract Group decision making takes place in almost all domains. In building construction domain, a team of contractors with disparate specializations collaborate. Little research has been done to propose group decision making technique for this domain. As such, specific teams’ competitiveness enhancements are minimal as it takes more time for individual evaluators to choose the right partners. Qualitative and quantitative methods were used. Themes and categorizations were based on deductive approach. Subsequently, Group Fuzzy Analytical Hierarchy Process (GFAHP), Multi-Criteria Decision Making (MCDM) algorithm, was designed and applied. It uses all evaluation criteria unlike Fuzzy AHP (FAHP) which excludes some criteria that are assigned zero weights. GFAHP reduces the number of pairwise comparisons required when a large number of attributes are to be compared. Validation of the technique carried out by five case studies, show that GFAHP is approximately 98.7% accurate in the selection of partners. en_US
dc.publisher International Conference on Information and Communication Technology for Development for Africa en_US
dc.relation.ispartofseries Volume 244;
dc.subject Multi criteria decision making Group Fuzzy Analytical Hierarchy Process Partners evaluation and selection problem en_US
dc.title Towards Group Fuzzy Analytical Hierarchy Process en_US


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