TY - JOUR ID - 20585 TI - Group multiple criteria ABC inventory classification using the TOPSIS approach extended by Gaussian interval type-2 fuzzy sets and optimization programs JO - Scientia Iranica JA - SCI LA - en SN - 1026-3098 AU - Mohammadghasemi, A. AU - Hadi-Vencheh, A. AU - Hosseinzadeh Lotfi, F. AU - Khalilzadeh, M. AD - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran AD - Department of Mathematics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran AD - Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran Y1 - 2019 PY - 2019 VL - 26 IS - 5 SP - 2988 EP - 3006 KW - Multiple criteria ABC inventory classification KW - Gaussian interval type-2 fuzzy sets KW - TOPSIS DO - 10.24200/sci.2018.5539.1332 N2 - The traditional ABC inventory classification is one of such approaches in which items are classified into three classes: A, very important; B, moderately important; and C, relatively unimportant based on annual dollar usage. However, other qualitative or quantitative criteria in real world may affect grouping items in the ABC inventory classification. Hence, multiple criteria ABC inventory classification (MCABCIC) is applied to classify items, instead of using the traditional ABC inventory classification. Hence, it can be taken into account as a multiple-criteria decision making (MCDM) problem due to using different criteria. The aim of this paper is to the extent TOPSIS approach with Gaussian interval type-2 fuzzy sets (GIT2FSs) as an alternative to the traditional triangular membership functions (MFs) for the MCABCIC in which GIT2FSs are more suitable for stating curved MFs. For this purpose, a new limit distance is presented for prioritizing GIT2FSs which is based on alpha cuts. The proposed method determines the positive and negative ideal solutions as left and right reference limits and then calculates distances between assessments and these limits. In our approach, the weights of the quantitative and qualitative criteria are attained via two linear programming, respectively. The model is illustrated using a real case. UR - https://scientiairanica.sharif.edu/article_20585.html L1 - https://scientiairanica.sharif.edu/article_20585_a83e583fa8daca32203ffafaecb490e7.pdf ER -