| 摘要: |
| 针对冷链物流配送系统中总成本较高以及车辆有效利用率低的问题，在考虑拥堵指数的基础上，构建以包含碳排放在内的配送总成本最小化和客户满意度最大化为总目标的多车型路径优化模型。采用自适应遗传模拟退火算法，对带有时间窗的冷链物流路径优化问题进行研究。结果表明:1)在配送总成本和客户满意度被视为同等重要的前提下，与采用配送总成本最低的单车型相比，多车型配送的满意度提高1.28%，总目标降低 31.40%；与采用满意度最高的单车型相比，多车型的配送总成本降低20.01%，总目标降低38.80%。因此，在上述前提下，多车型相比单车型配送更具优越性。2)与采用传统遗传算法相比，自适应遗传模拟退火算法在配送总成本上降低3.52%，满意度提高29.54%，且能较快求得最优解，验证了该算法的有效性；3)根据模型参数对各目标函数值的影响分析可得，适当的定价可提高满意度，降低碳排放量和货损成本；保质期的增长虽然降低了货损成本，但是会增加制冷成本和时间窗惩罚成本；生鲜农产品对时间敏感度的增加，会增大货损成本，但时间敏感度与配送总成本不成正相关。 |
| 关键词: 冷链物流 多车型 拥堵指数 碳排放 车辆路径优化 |
| DOI：10.11841/j.issn.1007-4333.2021.07.12 |
| 投稿时间：2020-10-31 |
| 基金项目:国家自然科学基金项目(71501125)；上海市教委重点项目(12ZZ167) |
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| Route optimization of multi-vehicle cold chain logistics for fresh agricultural products |
|
LI Juntao,LIU Mingyue,LIU Pengfei
|
| (College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China) |
| Abstract: |
| In view of the problems of high total cost and low utilization effect of vehicles in cold chain logistics distribution system, based on the consideration of traffic congestion, a multi-vehicle routing optimization model was established to minimize total distribution cost including carbon emission and maximize customer satisfaction. By using adaptive genetic simulated annealing algorithm, the routing optimization problem of cold-chain logistics with time window was investigated. The results showed that: 1)Under the premise that total distribution cost and customer satisfaction are considered equally important. Compared with the single vehicle with the lowest total distribution cost, the satisfaction of multi-vehicle distribution increased by 1. 28%, and the total objective function decreased by 31. 40%. Meanwhile, compared with the single model with the highest satisfaction, the total distribution cost of multi-vehicle decreased by 20. 01%, and the total objective function reduced by 38. 80%. Therefore, under the above premise, multi-model is more advantageous than single model distribution; 2)Compared with the traditional genetic algorithm, the adaptive genetic simulated annealing algorithm reduced the total cost of distribution by 3. 52% and improved the satisfaction by 29. 54%. Moreover, the optimal solution can be obtained faster, which verifies the effectiveness of the algorithm; 3)According to the analysis of the influence of model parameters on the value of each objective function, it can be obtained that appropriate pricing can improve satisfaction and reduce carbon emissions and goods loss costs. Although the increase of shelf life reduced the damage cost, it caused the increase of refrigeration cost and time window penalty cost; . The increase of the time sensitivity of fresh agricultural products will increase the cost of goods damage, but the time sensitivity is not positively correlated with the total distribution cost. |
| Key words: cold-chain logistics multi-vehicle congestion index carbon emission vehicle routing optimization |
