Optimizing Pricing and Inventory for Perishable Goods in Closed-Loop Supply Chains with SSMD Strategy | ||
| Journal of Quality Engineering and Production Optimization | ||
| مقاله 5، دوره 9، شماره 2، اسفند 2024، صفحه 107-132 اصل مقاله (1.94 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22070/jqepo.2025.19860.1290 | ||
| نویسندگان | ||
| Heibatolah Sadeghi* 1؛ Sahar Mansuri1؛ Mehdi Golbaghi2؛ Samin Arbabi3 | ||
| 1Department of industrial engineering, Faculty of engineering, University of Kurdistan, Sanandaj, Iran | ||
| 2Department of Technology and Engineering, Payame Noor University, Tehran, Iran | ||
| 3Department of industrial engineering, Faculty of engineering,University of Kurdistan, Sanandaj, Iran | ||
| چکیده | ||
| This paper proposes a comprehensive bi-level pricing-inventory model for closed-loop supply chains managing perishable goods with price-sensitive demand. The study addresses a critical gap in existing literature by integrating perishability constraints and pricing dynamics into a unified optimization framework. The proposed framework incorporates the Single Setup Multiple Delivery (SSMD) strategy, which enables manufacturers to optimize shipment frequencies and quantities, thereby minimizing inventory holding costs and mitigating perishability losses. Utilizing a hybrid mixed-integer optimization method that combines derivative-based techniques with integer search, the model identifies optimal pricing and inventory strategies to maximize supply chain profitability. A comprehensive sensitivity analysis is conducted to examine the interaction between manufacturer-retailer pricing strategies and evaluate the impact of key parameters on system performance. The results demonstrate the model’s effectiveness in addressing critical challenges, including the trade-off between shipment costs and perishability, while underscoring its potential to enhance profitability in perishable goods supply chains. Finally, future research directions are outlined, focusing on the integration of real-time data and machine learning for dynamic decision-making. | ||
| کلیدواژهها | ||
| Pricing؛ Inventory control؛ Integrated supply chain؛ Perishable items؛ Price-dependent demand | ||
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