Inventory optimization under tri phased demand with dual aging and controlled backlogging

The proposed study will create a unified inventory model that reduces the overall inventory cost and improves sustainability of seasonal and perishable goods. Seasonal and perishable inventories require superior models that are sensitive to the product attributes and fluctuating consumer demand. This article proposes a mathematical model in which both amelioration and deterioration phenomena are captured using a Weibull distribution and realistic product behavior is possible. The seasonal demand can be offered as a trapezoidal form of demand that varies with time and price, and a cubic holding cost form can be used to demonstrate the nonlinear rise in holding cost. The model also enables the backlogging of products to a certain degree in order to make shortages practical, and it includes investment in preservation to reduce the acceleration of the deterioration process and ensure quality of the product. Numerical examples and simulation studies under varying conditions of seasons confirm the model. The hybrid genetic algorithm (GA) and krill herd algorithm (KHA) optimization model proves to be very stable, computationally accurate with good convergence behavior, which justifies the practicability of the proposed model in the real world.