This study develops an inventory optimization model for perishable items using deteriorating inventory theory. The framework integrates time-dependent demand D ( t ) = Ae − αdt with Weibull-based hazard h ( t ) = αβ ( t − γ ) β −1 e − α ( t − γ ) β to characterize component non-instantaneous deterioration. The Time Shift Approach (TSA) is used to ensure that the functions are defined in the real domain. Shortages were allowed and partially backlogged. Numerical illustration was used to validate the model and Python script was employed to obtain the decision variables t 1 , t 2 and T as t 1 = 5.113399, t 2 = 5.163399 and T = 30.729455. Sensitivity analysis identifies demand rate ( α d ) and hazard variability ( σ ) as critical parameters. The minimal interval between t 1 and t 2 indicates that for items with high post-shelf-life deterioration, the optimal strategy requires rapid, sequential actions to preempt stockouts.
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Charlie et al. (2026) studied this question.
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