Sustainable cold supply chain management under demand uncertainty and carbon tax regulation.

• A two-stage stochastic programming model is developed to investigate the carbon emissions issue in cold supply chains under uncertain demand. • A matheuristic algorithm based on the Iterated Local Search (ILS) algorithm and a mixed integer programming is developed. • Optimal replenishment policies and transportation schedules are considered to minimize both operational and emissions costs. • The proposed model is applied to a real-world case study in Queensland, Australia. • It was found that high emissions price does not necessarily lead to an improvement in efficiency of the cold supply chain system. Increasing awareness of sustainability in supply chain management has prompted organizations and individuals to consider environmental impacts when managing supply chains. The issues concerning environmental impacts are significant in cold supply chains due to substantial carbon emissions from storage and distribution of temperature-sensitive product. This paper investigates the impact of carbon emissions arising from storage and transportation in the cold supply chain in the presence of carbon tax regulation, and under uncertain demand. A two-stage stochastic programming model is developed to determine optimal replenishment policies and transportation schedules to minimize both operational and emissions costs. A matheuristic algorithm based on the Iterated Local Search (ILS) algorithm and a mixed integer programming is developed to solve the problem in realistic sizes. The performance and robustness of the matheuristic algorithm are analyzed using test instances in various sizes. A real-world case study in Queensland, Australia is used to demonstrate the application of the model. The results highlight that higher emissions price does not always contribute to the efficiency of the cold supply chain system. Furthermore, the analyses indicate that using heterogeneous fleet including light duty and medium duty vehicles can lead to further cost saving and emissions reduction. [ABSTRACT FROM AUTHOR]