With the increasing security of food supply chains, ensuring the optimal transportation of perishable goods has become crucial. Various options and modes of transportation offer significant advantages in terms of efficiency, cost-effectiveness and environmental sustainability. However, the uncertainty associated with network structure and unforeseen events would pose unique challenges for optimising the food cold chain container routing. This research aims to develop a multi-objective optimisation model for the container-based food cold chain transportation system. Considering the random failure of the network nodes scenario, a container with a cold chain multimodal routing optimisation model was constructed. The optimisation goal is to minimise transportation costs, carbon emission costs and total transportation time. The research adopted a mixed-integer optimisation model by linearisation technology. Gurobi was used to solve the problem. The model and solution were then verified by the empirical data. The findings uncover the new influence of the node failure on the multimodal route design, as well as different parameters on the cost of multimodal routes for better decision-making. The research contributes to the development of more resilient and efficient food cold chain transportation systems through the new conditions of five constraints in the proposed model, which is capable of adapting to uncertainties in network structure and ad-hoc situations.
Chen et al. (Thu,) studied this question.