A meta-heuristic-based framework for sustainable P-hub network design of perishable items under fuzzy time uncertainty

In this paper, a novel mathematical model is presented for designing a sustainable hub network for perishable commodity transportation, taking into account social responsibility, environmental impact, and economic viability. As many real world problems have non-deterministic parameters, the time parameters are considered fuzzy numbers in the model. To validate the model, the model is solved on a small scale using GAMS software after linearisation. However, due to the non-deterministic polynomial time nature of the problem, an efficient meta-heuristic algorithm is proposed using MATLAB software. The algorithm has been validated on small and medium scale instances using the AP and CAB datasets. The results show that the proposed NSGA-II algorithm achieves an average solution gap of 0.017% while significantly reducing computational time compared to exact methods. The proposed model and algorithm can assist decision makers in designing sustainable and efficient supply chain networks for perishable products.