A Two-Warehouse Inventory Model for Green Technology Investment: Deteriorating Items with Selling Price and Carbon Emissions

Managing deteriorating inventory in mechatronics presents numerous opportunities. In today's world, nearly every industry utilizes mechatronic tools and processes to slow deterioration, thereby reducing carbon emissions. Given the complexity of global warming, many countries are investing in various initiatives and promoting eco-friendly business practices to minimize carbon emissions. This study examines a two-warehouse inventory model for deteriorating goods that emit carbon. Our focus is on minimizing carbon-emitting items during transportation. Reducing emissions from deteriorating inventory requires a comprehensive strategy that involves multiple supply chain partners and prioritizes environmental sustainability. By adopting green technologies, companies can effectively lower carbon dioxide emissions. In this model, demand is influenced by selling price, and partial backlogging is also considered. Additionally, incorporating time-dependent holding costs enhances the model’s applicability. The primary goal of this study is to optimize overall cycle time and costs associated with green technology investments. By optimizing these factors, businesses can manage deteriorating inventory more efficiently while mitigating environmental impacts. Integrating all these elements, we propose an optimized inventory model for deteriorating goods, factoring in selling price and carbon emissions under green technology investment. The assumptions in this study suggest that the cost function is highly nonlinear, leading to a constrained optimization problem. The model is solved using an algorithm implemented in Mathematica software. A numerical example is provided to illustrate the model’s application, followed by a sensitivity analysis. Finally, the optimal solution is visually represented through a graphical illustration.

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Publication Details

Journal
European Journal of Pure and Applied Mathematics
Published
2025-05-01
DOI
https://doi.org/10.29020/nybg.ejpam.v18i2.5847
Citations
1
Primary Topic
Sustainable Supply Chain Management
Type
article
Field-Weighted Citation Impact
2.23
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article

A Two-Warehouse Inventory Model for Green Technology Investment: Deteriorating Items with Selling Price and Carbon Emissions

Rahul Shukla, Krishna Kummari, Ashfar Ahmed
1 citations
European Journal of Pure and Applied Mathematics
Sustainable Supply Chain Management
2.23
article

A Two-Warehouse Inventory Model for Green Technology Investment: Deteriorating Items with Selling Price and Carbon Emissions

Rahul Shukla, Krishna Kummari, Ashfar Ahmed
article en
1 citations

Abstract

Managing deteriorating inventory in mechatronics presents numerous opportunities. In today's world, nearly every industry utilizes mechatronic tools and processes to slow deterioration, thereby reducing carbon emissions. Given the complexity of global warming, many countries are investing in various initiatives and promoting eco-friendly business practices to minimize carbon emissions. This study examines a two-warehouse inventory model for deteriorating goods that emit carbon. Our focus is on minimizing carbon-emitting items during transportation. Reducing emissions from deteriorating inventory requires a comprehensive strategy that involves multiple supply chain partners and prioritizes environmental sustainability. By adopting green technologies, companies can effectively lower carbon dioxide emissions. In this model, demand is influenced by selling price, and partial backlogging is also considered. Additionally, incorporating time-dependent holding costs enhances the model’s applicability. The primary goal of this study is to optimize overall cycle time and costs associated with green technology investments. By optimizing these factors, businesses can manage deteriorating inventory more efficiently while mitigating environmental impacts. Integrating all these elements, we propose an optimized inventory model for deteriorating goods, factoring in selling price and carbon emissions under green technology investment. The assumptions in this study suggest that the cost function is highly nonlinear, leading to a constrained optimization problem. The model is solved using an algorithm implemented in Mathematica software. A numerical example is provided to illustrate the model’s application, followed by a sensitivity analysis. Finally, the optimal solution is visually represented through a graphical illustration.

European Journal of Pure and Applied MathematicsVol. 18(2)
University of Hyderabad (IN), GITAM University (IN), Walter Sisulu University (ZA)
Openalex Percentile: Top 12%
Sustainable Supply Chain Management
2.23
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