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<p>The selling price, green level, and warranty term of the product all affect demand in the manufacturing inventory model for deteriorating products under a preservation facility, which is proposed in this study. Customers’ growing concerns about sustainability, product warranty period, and green level which measures a product’s environmental friendliness are important factors influencing demand. The model optimizes key decision parameters, including pricing strategy, warranty period, green level,&#xa0;preservation investment cost and production time, while also considering the effect of product deterioration over time under a preservation facility. Two numerical examples are solved to validate the proposed model. Due to the high nonlinearity of the objective function, the Artificial Ecosystem-Based Optimizer algorithm is employed to solve the proposed optimization problem. Additionally, a set of other popular algorithms is used to compare and justify the obtained results. Based on the results, the Artificial Ecosystem-Based Optimizer algorithm outperforms other metaheuristic algorithms, as demonstrated through statistical experiments. The concavity of the objective function is illustrated with respect to different decision variables. Convergence graphs for solving the objective function using different algorithms are also presented. Finally, a sensitivity analysis is performed to draw useful conclusions and provide valuable managerial insights.</p>

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Investigation of a Green Production Inventory Model with Stock-Dependent Production Rate Under Preservation Investment and Artificial Ecosystem-Based Optimizer

  • 期刊论文

  • 发表日期：

    2025年6月21日

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  • Hachen Ali,
  • Gobinda Chandra Panda,
  • Ali Akbar Shaikh,
  • Adel Fahad Alrasheedi

摘要

The selling price, green level, and warranty term of the product all affect demand in the manufacturing inventory model for deteriorating products under a preservation facility, which is proposed in this study. Customers’ growing concerns about sustainability, product warranty period, and green level which measures a product’s environmental friendliness are important factors influencing demand. The model optimizes key decision parameters, including pricing strategy, warranty period, green level, preservation investment cost and production time, while also considering the effect of product deterioration over time under a preservation facility. Two numerical examples are solved to validate the proposed model. Due to the high nonlinearity of the objective function, the Artificial Ecosystem-Based Optimizer algorithm is employed to solve the proposed optimization problem. Additionally, a set of other popular algorithms is used to compare and justify the obtained results. Based on the results, the Artificial Ecosystem-Based Optimizer algorithm outperforms other metaheuristic algorithms, as demonstrated through statistical experiments. The concavity of the objective function is illustrated with respect to different decision variables. Convergence graphs for solving the objective function using different algorithms are also presented. Finally, a sensitivity analysis is performed to draw useful conclusions and provide valuable managerial insights.