A production inventory model for the deteriorating goods under COVID-19 disruption risk

The rapid onset of the COVID-19 epidemic has brought the manufacturing process to a halt. The problem is especially serious for deteriorating products because demand for these items is not consistent and the product's worth has diminished with time. Many deteriorating product industries are now looking for an appropriate and effective disruption recovery plan to help them recover. However, a survey of the literature suggests that there has been little research done on developing an effective inventory production model for deteriorating products exposed to COVID-19 pandemic risks. This research intends to develop a disruption recovery model that considers demand as a time-dependent quadratic function to find out the optimum number of orders. Two different heuristic algorithms named: Genetic Algorithm (GA) and Whale Optimization Algorithm (WOA) have been employed to solve the model and it has been found that WOA performs better in terms of convergence. The numerical findings indicate that the price inclination rate for the component price and selling price played a pivotal role to maximize net profit. It is expected that by employing the proposed model of this research, the industry managers will be greatly benefitted to obtain quick recovery from the COVID-19 disruption risk for the deteriorating goods and retain financial stability.