Following the breakout of the novel coronavirus disease 2019 (COVID-19), the government of India was forced to prohibit all forms of human movement. It became important to establish and maintain a supply of commodities in hotspots and containment zones in different parts of the country. This study critically proposes new exponential similarity measures to understand the requirement and distribution of commodities to these zones during the rapid spread of novel coronavirus (COVID-19) across the globe. The primary goal is to utilize the important aspect of similarity measures based on exponential function under Pythagorean fuzzy sets, proposed by Yager. The article aims at finding the most required commodity in the affected areas and ensures its distribution in hotspots and containment zones. The projected path of grocery delivery to different residences in containment zones is determined by estimating the similarity measure between each residence and the various necessary goods. Numerical computations have been carried out to validate our proposed measures. Moreover, a comparison of the result for the proposed measures has been carried out to prove the efficacy.

中文翻译：

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毕达哥拉斯模糊集下 COVID-19 大流行期间隔离区商品供应的指数相似性度量的表现


2019 年新型冠状病毒病 (COVID-19) 爆发后，印度政府被迫禁止一切形式的人员流动。在该国不同地区的热点和隔离区建立和维持商品供应变得非常重要。这项研究批判性地提出了新的指数相似性测量方法，以了解新型冠状病毒（COVID-19）在全球快速传播期间对这些区域的商品需求和分配。主要目标是利用 Yager 提出的毕达哥拉斯模糊集下基于指数函数的相似性度量的重要方面。本文旨在寻找受影响地区最需要的商品，并确保其在热点地区和隔离区的分配。通过估计每个住宅和各种必需品之间的相似性度量来确定杂货配送到隔离区内不同住宅的预计路径。已经进行了数值计算来验证我们提出的措施。此外，还对所提出措施的结果进行了比较，以证明其有效性。