Trade-offs between economic and environmental goals of production-inventory-routing problem for multiple perishable products. (April 2023)

• Record Type: Journal Article
• Authors: Sun, Huali; Sun, Suning; Zhou, Yi; Xue, Yaofeng
• Is Part Of: Computers & industrial engineering. Volume 178(2023)
• Publication Date: 2023-04
• Subjects: Production-inventory-routing -- Multiple perishable products -- Carbon emissions -- Value loss; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2023.109133
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: An integrated production-inventory-routing problem for multiple perishable products and multiple vehicles is proposed. Two models are introduced to investigate the trade-offs between total emissions versus total costs. A particle swarm optimization (PSO) based method is designed to solve the models. Computational experiments illustrate the routing stage is the most important activity for two models. Sensitivity analysis shows that the perishable product's shelf life has a significant effect on total costs and total emissions. Abstract: In this paper, we study an integrated production-inventory-routing problem for multiple perishable products (MPPIRP). We introduce two models to evaluate the trade-off between total emissions and total costs. The first model concentrates on minimizing carbon emissions from production, inventory, and routing activities. Notably, carbon emission in transportation depends on several factors, including vehicle load (empty load and carried load), velocity, and traveled distance. The other model considers the value loss of products due to deterioration during their lifetime in the total cost minimization objective function. We impose constraints that perishable products cannot be held, delivered, or used after their lifetimes have expired in both models. Then, we devise a PSO-based method to solve them. Computational experiments verify the effectiveness of the PSO-based method and the rationality of models. Furthermore, we compare costs, emissions, and key performance indicators under both objective functions. The impact of shelf-life on both objectives also has been analyzed. Computational results help us gain significant insights on generating strategy of production, inventory, and routing to minimize total costs or achieve a fully environmental-friendly goal.