Mass public quarantining, colloquially known as a lock-down, is a non-pharmaceutical intervention to check spread of disease. This paper presents ESOP (Epidemiologically and Socio-economically Optimal Policies) 1 , a novel application of active machine learning techniques using Bayesian optimization, that interacts with an epidemiological model to arrive at lock-down schedules that optimally balance public health benefits and socio-economic downsides of reduced economic activity during lock-down periods. The utility of ESOP is demonstrated using case studies with VIPER (Virus-Individual-Policy-EnviRonment), a stochastic agent-based simulator that this paper also proposes. However, ESOP is flexible enough to interact with arbitrary epidemiological simulators in a black-box manner, and produce schedules that involve multiple phases of lock-downs. Disclaimer: This paper makes no recommendation to individuals and its results should not be interpreted by individuals to modulate personal behavior. The authors recommend that individuals continue to follow guidelines offered by local governments with respect to lock-downs and social distancing, and those offered by medical professionals with respect to personal hygiene and treatment.

Due to rapid globalization, an introduction of Goods and Services Taxes (GST), ban on BS-III vehicles, and rapid technological advancement creates new dimensions for the automobile industry in India especially for those who come in the category of small and medium enterprise (SMEs).In the current changing scenario victorious execution of supply chain management (SCM) practices can provide competitive leverage to Automobile manufacturers over their rivals particularly those who are poorly implemented supply chain management practices. This paper takes two main SCM practices, i.e. supply chain flexibility (SCF) and supply chain strategy (SCS).Against this background, this paper acknowledged 5 success factors (SFs) for supply chain flexibility and 3 success factors (SFs) for supply chain strategy for proper implementation of SCM practices in the Automobile industry, and studied their impact on three factors of supply chain performance (SCP), and thereby on firms performance. The top management of any industry is focused on their core strength with commitment, long-term vision and provides resources for supply chain, and thereby developing effective and efficient SCS emerged as the most significant SFs. To measure the impact on supply chain performance, the author carefully measures different SFs of SCS related to customer-oriented strategy, innovation strategy and agile supply chain strategy on cost performance, logistics performance and customer satisfaction performance. Similarly to access the impact on supply chain performance, carefully measure different SFs of SCF on cost performance, logistics performance and customer satisfaction performance. Results are analyzed by testing research propositions using standard statistical tools.

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