Sci Rep. 2025 Aug 4;15(1):28459. doi: 10.1038/s41598-025-13565-4.
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.
PMID:40760143 | DOI:10.1038/s41598-025-13565-4
