This paper Optimizes the inventory stock model that aligns with the real-world complexities by including salvage value into the analysis of deteriorating or decaying goods. Its extents the study done in the research work done by Sharma, G., & Vyas, B. On optimization of inventory cost using the EOQ model taking linear demand and the Weibull decay distribution of the items and the concept of partial backlogging. We have further added salvage value in this research work. Rate of demand is taken as to vary linearly over time. The deterioration rate of system’s inventory follows a Weibull distribution, reflecting a more flexible and realistic inventory decay behaviour. Also, the model accounts for partial backlogging, considering the fact that not all unmet demand can be satisfied. Our main motive of this paper is to minimize overall inventory cost by obtaining the value of optimal quantity of order and cycle length under these taken dynamic conditions. All the analytical and graphical calculations are solved with the help of mathematical software , also a numerical demo example is solved to observe the overall effect of salvage value on cost elements of the inventory model and the inventory decision variables. Sensitivity analysis is also performed to explain how the key inventory parameters are affecting the optimal strategy, giving valuable results for inventory planning in perishable or decaying goods and time dependent inventory environments.
Vyas et al. (Mon,) studied this question.