Optimizing carbon reduction and vehicle routing for small-portion meal delivery under dual carbon goals

Abstract

The burgeoning trend of small-portion meals, offering two-thirds or less of a standard-portion, is a crucial strategy to reduce carbon emissions and food waste in the food delivery sector. This study introduces a comprehensive measurement framework encompassing meal preparation, packaging, delivery, and waste management processes. We formulate four models—Total-Curb, Dual-Curb, Equal-Curb, and Elite-Curb—targeting different carbon emission control goals. To address the complexities of these models, we design a trajectory similarity measure with driver familiarity for order allocation. Additionally, an adaptive iterative neighborhood search algorithm has been developed, incorporating neighborhood operators and heuristic rules to enhance solution quality and efficiency. A case study in Dalian, China, employs six comparative indicators to estimate the carbon reduction impact of small-portion meals. Our findings reveal that small-portion meals contribute significantly to carbon reduction in all models except the Elite-Curb model. Among them, the Dual-Curb model emerges as a balanced solution, offering a compromise between carbon emission reduction and operational efficiency, while the Elite-Curb model is less effective. The adoption of small-portion meals stands as a potent low-carbon transportation solution for online meal delivery platforms, promoting a more environmentally conscious and sustainable industry paradigm.