Abstract
Measuring the carbon emissions of logistics in online retailing is crucial for global decarbonization efforts. Large-scale online supermarkets now constitute a significant share of the entire online retail industry. To decrease the cost and carbon emission and examine their involvement in carbon trading in China, the paper presents a solution procedure for the low-carbon two-echelon vehicle routing problem (LC2EVRP) of online supermarkets. First, a mixed integer programming model is built for the LC2EVRP. Then, the paper analyzes the rules and inherent relations of the two stages of LC2EVRP. The pre-assignment genetic algorithm hybridized variable neighborhood search algorithm (PAGA-VNS) is built to address the LC2EVRP. Its pre-assignment customers are based on the principle of proximity and employ a neighborhood search strategy to perturbed assignment. Finally, with a real large-scale online supermarket as the background, numerical cases are constructed to demonstrate the efficiency of the solution algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 261-272 |
| Number of pages | 12 |
| Journal | International Journal of Innovative Computing, Information and Control |
| Volume | 21 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2025 |
Keywords
- Genetic algorithm
- Low-carbon
- Neighbourhood search algorithm
- Online supermarket
- Two-echelon vehicle routing problem
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