ERP software selection problem with a novel Hybrid hesitant fuzzy cross-entropy and probabilistic hesitant fuzzy MCDM approach

2025-01-01
Akpinar, Ipek
Kececi, Baris
Atalay, Kumru
Boran, Melis
This paper aims to develop a novel hesitant fuzzy weighting method combined with probabilistic hesitant fuzzy COPRAS and to apply the proposed algorithm to a real-life ERP software selection problem. The proposed algorithm has two stages. First, the weights of evaluation criteria are determined via the hesitant fuzzy cross-entropy weighting method using different distance measures. Then, the ranking of alternatives is obtained by probabilistic hesitant fuzzy COPRAS. Six qualitative criteria are considered in the application, and the three alternatives are ranked using different cross-entropy and distance measures. The results are compared with those obtained from the COPRAS, fuzzy COPRAS and hesitant fuzzy COPRAS methods. The application results show that the proposed algorithm is helpful in ranking alternatives with each entropy and distance measure. As far as the authors know, no method combines probabilistic hesitant fuzzy COPRAS with hesitant fuzzy cross-entropy with various distance metrics exists.
Journal of Industrial and Management Optimization
Citation Formats
I. Akpinar, B. Kececi, K. Atalay, and M. Boran, “ERP software selection problem with a novel Hybrid hesitant fuzzy cross-entropy and probabilistic hesitant fuzzy MCDM approach,” Journal of Industrial and Management Optimization, vol. 21, no. 9, pp. 5662–5686, 2025, Accessed: 00, 2025. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105015818807&origin=inward.