Warehouse performance measurement is of great importance for the development of companies. The companies are to measure their current situation in order to attain ability relating to realizing the improvement process. In this measurement phase, they have to decide what is considered and what proportion it is done. In this study, the most effective factors were determined using the interval type-2 fuzzy analytic hierarchy process method for the factor values that are effective in warehouse performance measurement. The reason to use this solution method is that because of having 3 dimensional membership function, type-2 fuzzy clusters reflect more uncertainties in decision-making problems than type-1 fuzzy clusters do.
Eser Adı (dc.title) | Interval Type-2 Fuzzy Analytic Hierarchy Process Application on Warehouse Performance Measurement Criteria Defined |
Yayın Türü (dc.type) | Konferans Bildirisi |
Yazar/lar (dc.contributor.author) | YAŞAR, Esra |
Yazar/lar (dc.contributor.author) | ARAS, Nil |
Atıf Dizini (dc.source.database) | Diğer |
Konu Başlıkları (dc.subject) | Fuzzy Analytic Hierarchy Process |
Konu Başlıkları (dc.subject) | Warehouse Performance Management |
Konu Başlıkları (dc.subject) | Type-2 |
Yayıncı (dc.publisher) | 3rd International Conference on Computational Mathematics and Engineering Science (CMES 2018) |
Yayın Tarihi (dc.date.issued) | 2018 |
Kayıt Giriş Tarihi (dc.date.accessioned) | 2019-07-10T13:03:20Z |
Açık Erişim tarihi (dc.date.available) | 2019-07-10T13:03:20Z |
Özet (dc.description.abstract) | Warehouse performance measurement is of great importance for the development of companies. The companies are to measure their current situation in order to attain ability relating to realizing the improvement process. In this measurement phase, they have to decide what is considered and what proportion it is done. In this study, the most effective factors were determined using the interval type-2 fuzzy analytic hierarchy process method for the factor values that are effective in warehouse performance measurement. The reason to use this solution method is that because of having 3 dimensional membership function, type-2 fuzzy clusters reflect more uncertainties in decision-making problems than type-1 fuzzy clusters do. |
Yayın Dili (dc.language.iso) | en |
Tek Biçim Adres (dc.identifier.uri) | https://hdl.handle.net/20.500.12498/1153 |