A Bi-Objective Green Location-Routing Problem Under Carbon Tax Policies

In response to the highly competitive market and the demand for a low-carbon economy, logistics enterprises have paid special attention not only to cost management but also to environmental sustainability for better development. In such context, this study seeks to investigate a Green Location Routing Problem (GLRP) and develops a bi-objective model with the aim of minimizing total costs and carbon emissions. For the solution approach, various multi-objective optimization methods were compared initially, and Non-dominated sorting genetic algorithm II (NSGA-II) was finally selected for use in this study. The model’s applicability is assessed through adapted benchmark instances. A real-world case study further evaluates the impact of carbon tax, highlighting the model’s practical value and effectiveness. Experimental results reveal that the carbon tax policy is effective in reducing carbon emissions in scenarios that focus on minimizing total costs, yet it has no effect in CO2 minimization scenarios; incremental increases in carbon tax levels make the two objectives converge, ultimately yielding a singular, optimized solution. This study offers practical and managerial insights for logistics enterprises and contributes to a better understanding of the interplay between carbon tax policies and logistics decision-making.