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The Covid-19 epidemic has caused substantial obstacles to the supply network globally. Hence there is urgency and necessity to build a model for cash flow in the chain of demand and supply system. This research suggests an inventory model to assist retailers in determining the optimal ordering quantity and replenishment cycle to reduce the total cost in different payment cases. The current study looks toward a partial advance and delays in the payment system considering time-sensitive demand, shortage, and partial backlogging for instantaneous deteriorating items. During the financial crisis, the partial advance and delay-in-payment strategy is planned to keep orders flowing from retailers to suppliers and customers to retailers. The impact of advanced and delayed payments on the total cost of a retailer is examined. To exemplify the model’s application, numerical examples are used. A sensitivity study of critical parameters has been done to identify more sensitive parameters which reveal the clear depiction of present problems.

This article proposes a novel approach to managing inventory by incorporating machine learning techniques to handle imperfect deteriorating products under green investment technology. The shortages are permitted and partially backlogged. Due to uncertainty, deterioration rate and defective percentage in quantity in the received lot are considered fuzzy variables. This study aims to determine optimal ordering quantity and replenishment period to minimise the total average cost with carbon emission cost. Decision Tree Classifier algorithm is used to demand forecast seasonally. The total fuzzy cost functions defuzzify by applying sign distance approach method. A numerical example is taken to illustrate the proposed model. A comparative analysis has been studied between fixed demand and month-wise forecasted demand. The study highlights the importance of forecasted demand in the inventory system and establishes methodology to get direct month-wise forecasted demand. Finally, the sensitivity analysis performs to determine more sensitive parameters and provides managerial insights. [ABSTRACT FROM AUTHOR]