Mixed fleet-based two-echelon vehicle routing optimization for cold chain logistics with diverse recharging strategies

Abstract

The expansion of cold chain logistics necessitates a substantial fleet of fuel-refrigerated trucks, which presents environmental challenges. Electric vehicles (EVs) offer an environmentally friendly solution for low-carbon development despite the issue of range anxiety. Diverging from the conventional two-echelon distribution structure, this paper explores alternative recharging strategies and introduces an innovative scheme: employing fuel vehicles in suburban areas and EVs in urban central zones. The presented model optimizes economic and environmental considerations to mitigate air pollution and reduce dependence on non-renewable energy sources while providing feasible routes. This study proposes an allocation algorithm and an enhanced ant colony algorithm to address a single-objective two-echelon vehicle routing problem with the mixed fleet (2EVRPMF). The mixed fleet outperforms in terms of both cost and carbon emissions based on numerical experiments. Additionally, the study investigates the influence of battery capacity and recharging rate under various recharge strategies, including their correlation with costs. The findings can provide valuable insights for decision-making in implementing environmentally-friendly logistics within the cold chain industry.