Analyzing the nature of a transportation problem before and during COVID-19 pandemic in multi-fuzzy environment

In the twenty-first century, an unprecedented shock to both the public and freight transportation is the outbreak of the COVID-19 (coronavirus disease of 2019) pandemic. All the affected countries have decided on a complete lockdown to reduce the transmission of coronavirus. After that time, all those affected countries have started the transportation system following some rules and regulations. In this paper, we have studied a transportation model considering the covid issues. That problem has been comparatively analyzed with a classical transportation problem. Here, two conflicting objective functions namely transportation and sanitization costs are considered and both are minimized simultaneously. To identify the intensification of coronavirus at different locations of sources or destinations, a function namely ‘COVID-19 intensity’ has been introduced. On the basis of this function value, the sanitization cost has been determined at different locations. Due to uncertainty in covid parameters which are collected from different health organizations, the model has been constructed in a triangular multi-fuzzy environment. Also, to obtain an equivalent deterministic form of the uncertain model in multi-fuzzy environment, an existing approach namely the weighted averaging based on levels method has been extended using Maclaurin series expansion. Finally, some examples are considered to study the feasibility of the proposed models.