A GREY WOLF OPTIMIZER FOR ESTIMATING THE STOCHASTIC SIRD AND OPTIMIZING A REGIME-SWITCHING CASH FLOW MODEL

The COVID-19 pandemic has significantly impacted various sectors, including industries. Companies have struggled with operational risks while striving to optimize their cash flows. To address the financial challenges posed by the pandemic, we propose a novel cash flow model that aims to determine the optimal profit for a company. This model operates based on two distinct states or regimes: mothballing (temporary suspension of operations) and reactivating conditions. The regime-switching is determined by the number of infected employees in the company which is estimated based on the stochastic SIRD model. Leveraging insights from the stochastic SIRD model, we employ a grey wolf optimizer to estimate key parameters in the stochastic SIRD and subsequently the cash flow model. In conclusion, our approach allows us to estimate the optimal timing for implementing mothballing or reactivating strategies accurately, taking into account the number of infected employees. By doing so, companies can make informed decisions to maximize profit while safeguarding employee well-being.