<p>This study introduces an innovative inventory model for non-instantaneously deteriorating items with time-varying demand, integrating inflation, preservation technology, and carbon emissions. The model strategically utilizes port-provided free storage periods to minimize holding costs and delay financial commitments, replacing traditional reliance on owned or rented storage. It also incorporates green technology to reduce carbon emissions from transportation, promoting environmental sustainability. Numerical experiments conducted with MATLAB confirm the model’s effectiveness: the optimal strategy (Model 1) yields a minimum total inventory cost of $134,150, with optimal decision variables <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41660_2025_542_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="72" /> </InlineMediaObject> <EquationSource Format="TEX">$t_2 = 28.59$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mi>t</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>28.59</mn> </mrow> </math></EquationSource> </InlineEquation> days, <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41660_2025_542_Article_IEq2.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="72" /> </InlineMediaObject> <EquationSource Format="TEX">$T = 98.44$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>T</mi> <mo>=</mo> <mn>98.44</mn> </mrow> </math></EquationSource> </InlineEquation> days, and preservation investment <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41660_2025_542_Article_IEq3.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="70" /> </InlineMediaObject> <EquationSource Format="TEX">$\eta = 44.97$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>η</mi> <mo>=</mo> <mn>44.97</mn> </mrow> </math></EquationSource> </InlineEquation>. Comparative analyses reveal that excluding carbon emissions, inflation, green technology, or preservation investment leads to significant cost increases—up to 53.32% higher than the optimal configuration—underscoring the importance of each factor. Sensitivity analysis shows that parameters such as inflation rate, deterioration rate, and preservation investment substantially influence total cost, while purchasing cost and demand base rate have marginal effects. These results offer actionable insights for supply chain managers aiming to reduce costs while improving sustainability. The proposed model provides a comprehensive and robust framework for managing time-sensitive goods in modern logistics networks.</p>

Optimal Utilization of Port-free-of-charge for Inventory Management with Inflation, Preservation Technology, and Carbon Emissions

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发表日期：

2025年6月20日

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Anthony Limi,
K. Rangarajan

摘要

This study introduces an innovative inventory model for non-instantaneously deteriorating items with time-varying demand, integrating inflation, preservation technology, and carbon emissions. The model strategically utilizes port-provided free storage periods to minimize holding costs and delay financial commitments, replacing traditional reliance on owned or rented storage. It also incorporates green technology to reduce carbon emissions from transportation, promoting environmental sustainability. Numerical experiments conducted with MATLAB confirm the model’s effectiveness: the optimal strategy (Model 1) yields a minimum total inventory cost of $134,150, with optimal decision variables $t_2 = 28.59$ $t_{2} = 28.59$ days, $T = 98.44$ $T = 98.44$ days, and preservation investment $\eta = 44.97$ $η = 44.97$ . Comparative analyses reveal that excluding carbon emissions, inflation, green technology, or preservation investment leads to significant cost increases—up to 53.32% higher than the optimal configuration—underscoring the importance of each factor. Sensitivity analysis shows that parameters such as inflation rate, deterioration rate, and preservation investment substantially influence total cost, while purchasing cost and demand base rate have marginal effects. These results offer actionable insights for supply chain managers aiming to reduce costs while improving sustainability. The proposed model provides a comprehensive and robust framework for managing time-sensitive goods in modern logistics networks.