Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm

Abstract This study develops a comprehensive inventory model for deteriorating items by incorporating preservation technology and addressing sustainability-driven customer behavior. Demand is modeled as a nonlinear function influenced by three key factors: selling price, green level (reflecting the...

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Main Authors: Hachen Ali, Gobinda Chandra Panda, Adel Fahad Alrasheedi, Ali Akbar Shaikh, Jeonghwan Gwak
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-13565-4
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author Hachen Ali
Gobinda Chandra Panda
Adel Fahad Alrasheedi
Ali Akbar Shaikh
Jeonghwan Gwak
author_facet Hachen Ali
Gobinda Chandra Panda
Adel Fahad Alrasheedi
Ali Akbar Shaikh
Jeonghwan Gwak
author_sort Hachen Ali
collection DOAJ
description Abstract This study develops a comprehensive inventory model for deteriorating items by incorporating preservation technology and addressing sustainability-driven customer behavior. Demand is modeled as a nonlinear function influenced by three key factors: selling price, green level (reflecting the environmental friendliness of the product and its production), and available inventory level. Recognizing rising environmental consciousness, the green level directly shapes consumer demand, while preservation investment reduces deterioration and extends the shelf life of perishable goods. The objective of the model is to maximize the total profit by jointly optimizing five decision variables: selling price, green level investment, preservation effort, cycle length, and replenishment quantity. The resulting objective function is highly nonlinear and complex. To solve it efficiently, this study employs the Marine Predators Algorithm (MPA)—a newly developed metaheuristic algorithm well-suited for continuous, nonlinear optimization. Model authenticity is established through a combination of sensitivity analysis, convergence behavior examination, and validation against benchmark test problems from existing literature. The robustness of the solution method is further demonstrated by comparing the MPA’s performance with other optimization techniques in terms of solution quality and computational efficiency. Although the study is theoretical in nature, data assumptions are grounded in real-world parameter ranges drawn from validated case studies and academic sources. Parameters such as deterioration rates, green investment cost coefficients, and preservation effectiveness are selected to reflect practical supply chain conditions. This ensures the credibility of the model output and applicability in realistic scenarios. The study offers critical managerial insights, including how to balance sustainability initiatives, pricing decisions, and preservation investments for optimal inventory control. These insights are particularly valuable for supply chains dealing with environmentally sensitive, perishable products, helping businesses enhance operational efficiency while supporting green objectives.
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spelling doaj-art-6adf48b442b44c6496107d7b7bef01e32025-08-20T03:42:22ZengNature PortfolioScientific Reports2045-23222025-08-0115112210.1038/s41598-025-13565-4Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithmHachen Ali0Gobinda Chandra Panda1Adel Fahad Alrasheedi2Ali Akbar Shaikh3Jeonghwan Gwak4Department of Mathematics, The University of BurdwanDepartment of Operations Management, Biju Patnaik Institute of IT & Management StudiesDepartment of Statistics and Operations Research, College of Science, King Saud UniversityDepartment of Mathematics, The University of BurdwanDepartment of Biomedical Engineering, Korea National University of TransportationAbstract This study develops a comprehensive inventory model for deteriorating items by incorporating preservation technology and addressing sustainability-driven customer behavior. Demand is modeled as a nonlinear function influenced by three key factors: selling price, green level (reflecting the environmental friendliness of the product and its production), and available inventory level. Recognizing rising environmental consciousness, the green level directly shapes consumer demand, while preservation investment reduces deterioration and extends the shelf life of perishable goods. The objective of the model is to maximize the total profit by jointly optimizing five decision variables: selling price, green level investment, preservation effort, cycle length, and replenishment quantity. The resulting objective function is highly nonlinear and complex. To solve it efficiently, this study employs the Marine Predators Algorithm (MPA)—a newly developed metaheuristic algorithm well-suited for continuous, nonlinear optimization. Model authenticity is established through a combination of sensitivity analysis, convergence behavior examination, and validation against benchmark test problems from existing literature. The robustness of the solution method is further demonstrated by comparing the MPA’s performance with other optimization techniques in terms of solution quality and computational efficiency. Although the study is theoretical in nature, data assumptions are grounded in real-world parameter ranges drawn from validated case studies and academic sources. Parameters such as deterioration rates, green investment cost coefficients, and preservation effectiveness are selected to reflect practical supply chain conditions. This ensures the credibility of the model output and applicability in realistic scenarios. The study offers critical managerial insights, including how to balance sustainability initiatives, pricing decisions, and preservation investments for optimal inventory control. These insights are particularly valuable for supply chains dealing with environmentally sensitive, perishable products, helping businesses enhance operational efficiency while supporting green objectives.https://doi.org/10.1038/s41598-025-13565-4InventoryDeteriorationSelling priceGreen productPreservationPartially backlogged shortages
spellingShingle Hachen Ali
Gobinda Chandra Panda
Adel Fahad Alrasheedi
Ali Akbar Shaikh
Jeonghwan Gwak
Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm
Scientific Reports
Inventory
Deterioration
Selling price
Green product
Preservation
Partially backlogged shortages
title Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm
title_full Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm
title_fullStr Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm
title_full_unstemmed Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm
title_short Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm
title_sort greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm
topic Inventory
Deterioration
Selling price
Green product
Preservation
Partially backlogged shortages
url https://doi.org/10.1038/s41598-025-13565-4
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