An Inventory Model for Growing Items with Imperfect Quality, Deterioration, and Freshness- and Inventory Level-Dependent Demand Under Carbon Emissions

Inventory models have evolved to incorporate a wide range of realistic factors, including growing items, imperfect quality, deterioration, and sustainability concerns. While these areas have received significant individual attention, no model has yet integrated the complexities of growing items, imperfect quality, deterioration, and carbon emissions. This study addresses this gap by introducing an economic order quantity (EOQ) model for growing items that simultaneously accounts for imperfect quality, deterioration, carbon emissions, and a demand rate that is influenced by both stock levels and the freshness condition. The goal is to determine the replenishment cycle and the optimal order quantity that will maximise profit. A numerical example is presented to illustrate the model’s feasibility. A sensitivity analysis on key parameters is also conducted to provide critical managerial insights. The results reveal that the shelf life of items and the scaling parameter of demand are among the most influential factors of profit, causing up to 150% and 112% increase in profit, respectively. The findings also indicate that deterioration significantly impacts system profitability by up to −45%. Another critical insight is that profit decreases by up to 80% when the weight of the growing items increases. Furthermore, emissions can be most effectively reduced by focusing on the feeding process, which represents the most impactful factor for improving sustainability, whereas emissions from the screening process, purchasing, deterioration, and storage hold minimal financial consequence.

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Publication Details

Journal
AppliedMath
Published
2025-12-12
DOI
https://doi.org/10.3390/appliedmath5040181
Citations
1
Primary Topic
Supply Chain and Inventory Management
Type
article
Field-Weighted Citation Impact
2.28
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article

An Inventory Model for Growing Items with Imperfect Quality, Deterioration, and Freshness- and Inventory Level-Dependent Demand Under Carbon Emissions

1 citations
AppliedMath
Supply Chain and Inventory Management
2.28
article

An Inventory Model for Growing Items with Imperfect Quality, Deterioration, and Freshness- and Inventory Level-Dependent Demand Under Carbon Emissions

article en
1 citations

Abstract

Inventory models have evolved to incorporate a wide range of realistic factors, including growing items, imperfect quality, deterioration, and sustainability concerns. While these areas have received significant individual attention, no model has yet integrated the complexities of growing items, imperfect quality, deterioration, and carbon emissions. This study addresses this gap by introducing an economic order quantity (EOQ) model for growing items that simultaneously accounts for imperfect quality, deterioration, carbon emissions, and a demand rate that is influenced by both stock levels and the freshness condition. The goal is to determine the replenishment cycle and the optimal order quantity that will maximise profit. A numerical example is presented to illustrate the model’s feasibility. A sensitivity analysis on key parameters is also conducted to provide critical managerial insights. The results reveal that the shelf life of items and the scaling parameter of demand are among the most influential factors of profit, causing up to 150% and 112% increase in profit, respectively. The findings also indicate that deterioration significantly impacts system profitability by up to −45%. Another critical insight is that profit decreases by up to 80% when the weight of the growing items increases. Furthermore, emissions can be most effectively reduced by focusing on the feeding process, which represents the most impactful factor for improving sustainability, whereas emissions from the screening process, purchasing, deterioration, and storage hold minimal financial consequence.

AppliedMathVol. 5(4)
University of Pretoria (ZA)
Responsible consumption and production
Openalex Percentile: Top 8%
Supply Chain and Inventory Management
2.28
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