Designing a Green-Resilient Supply Chain Network for Perishable Products Considering a Pricing Reduction Strategy to Manage Optimal Inventory: A Column Generation-based Approach
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
This paper aims to design an integrated green supply chain by considering several drivers of resiliency for perishable products. Supply chain resiliency seeks to prevent the chain from moving toward unfavorable conditions and to manage and mitigate disruptions. To minimize the effects of disruption, new strategies are investigated, including horizontal cooperation between distribution centers, emergency inventory reserves in production and distribution centers, and contracts with backup suppliers. Additionally, to avoid resource wastage, the strategy of reducing the selling price of products nearing their expiration date is considered, allowing the model to control the optimal amount of production and inventory. In addition to resiliency, all supply chain members must adopt a green supply chain approach to conduct production and distribution activities in a manner that reduces environmental damage. Therefore, optimal routing is implemented to deliver products at the minimum possible cost and with the least pollution. A column generation decomposition algorithm is developed to improve solution time as the model becomes complex and unsolvable or takes a long time to solve with standard mixed-integer programming solvers. After designing an integrated supply chain for perishable products, we initially solved several test cases to determine the applicability of the column generation method to these issues. Subsequently, we employed the proposed solution method for a specific case study on the PEGAH dairy industry. A sensitivity analysis was conducted on the product's shelf life to examine variations in optimal production and inventory levels. The results indicated that as the product's lifetime decreases, a lower quantity of the product is produced and stored.
Keywords:
Language:
English
Published:
Journal of Quality Engineering and Production Optimization, Volume:8 Issue: 1, Winter-Spring 2023
Pages:
171 to 196
https://www.magiran.com/p2803842
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