Promoting sustainability of the integrated production-inventory-distribution system through the Physical Internet

Abstract

Owing to its interconnections and open characteristics, Physical Internet (PI) has the potential to help companies meet the sustainability challenges. In this paper, to investigate the sustainability performance of the PI in an integrated production-inventory-distribution system, we propose a multi-objective mixed integer linear programming model (MOMILP) that encompasses all three dimensions of sustainability. The economic and environmental objectives are measured through the total cost and greenhouse gas (GHG) emissions, respectively. The social objective is captured by the impact of accident risk. Then, we solve the model by using the augmented ϵ-constraint method and compare the sustainability performance of the PI-enabled model with that of models enabled by the traditional (TR) and horizontal collaboration (HC) networks. The results show that the PI can not only improve the economic and environmental performance by increasing vehicle utilisation, but also alleviate the impacts of accident risks by avoiding risky routes. More interestingly, good compromise solutions featuring the PI can further improve the sustainability performance while guaranteeing the performance of the TR at the ideal point—something unachievable for the HC and TR. Moreover, sensitivity analyses demonstrate that the PI can still guarantee significant sustainability performance advantages under different common retailer quantities and network structures.

Keywords:

• production-inventory-distribution
• sustainability
• Physical Internet
• multi-objective optimisation
• vehicle routing

Acknowledgments

This research was partially supported by the National Natural Science Foundation of China (Grant Numbers 71572031 and 71971049).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was partially supported by the National Natural Science Foundation of China (Grant Numbers 71572031 and 71971049).