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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在毕达哥拉斯模糊集下 COVID-19 大流行期间收容区商品供应的指数相似性度量的性能

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控制区建立和维持商品供应变得很重要。本研究批判性地提出了新的指数相似性度量，以了解在新型冠状病毒 (COVID-19) 在全球范围内快速传播期间商品对这些区域的需求和分布。主要目标是利用 Yager 提出的基于毕达哥拉斯模糊集下指数函数的相似性度量的重要方面。该文章旨在寻找受影响地区最需要的商品，并确保其在热点和收容区的分布。通过估计每个住宅与各种必需品之间的相似性度量，确定杂货配送到收容区不同住宅的预计路径。已经进行了数值计算以验证我们提出的措施。此外，对所提议措施的结果进行了比较，以证明其有效性。