Intuitionistic trapezoidal fuzzy prioritized weighted geometric operator: An algorithm for the selection of suitable treatment for lung cancer

Abstract

Lung cancer is considered as the second most common cancer and is the major cause of cancer deaths over the globe. Due to advancement in the field of medical science, different types of treatments or therapies are made available for the treatment of the disease. Multiple attribute group decision making (MAGDM) with the help of intuitionistic trapezoidal fuzzy (ITrF) information has wide applications in decision-making processes especially in the field of medical science. In this paper, we use the concept of MAGDM from a geometric point of view for selection of the most appropriate treatment from the available set of treatments for lung cancer as per the attributes. Once the disease has been diagnosed, with the help of the algorithm of intuitionistic trapezoidal fuzzy prioritized weighted geometric (ITFPWG) operators, we can select the most suitable treatment for lung cancer. Finally, we demonstrate the method by taking a hypothetical case study.