Akademik Veri Yönetim Sistemi
Journal of Multiple-Valued Logic and Soft Computing, cilt.38, sa.5-6, ss.575-602, 2022 (SCI-Expanded)
The pandemic spread of COVID-19 caused by a virus that affects the respiratory system represents a dramatic threat to life. People have been practicing social distancing by working from home in recent months since it is an excellent solution to reduce one’s exposure to COVID-19. However, many occupations do not have this chance due to the necessity to attend the workplace. Besides, some professions require close contact with infected people such as medicine and nursing, while others such as logging and gardening have a low level of risk in this respect. However, while occupations such as medicine and nursing can take precautions against the virus at a very good level, the knowledge of occupations such as logging and gardening is weak against it. Prioritizing occupations based on these conflicting criteria is an important task under the vagueness and impreciseness of human evaluations. In this paper, a novel fuzzy AHP & TOPSIS methodology is proposed, where the reliability and restriction of the expert assessments are considered by interval-valued type 2 fuzzy numbers. A real case study including five experts, 14 occupations, and seven criteria is presented. A comparative analysis is also given to validate the proposed methodology.