疫情防控背景下生鲜物资运输路径优化

 疫情防控背景下，消费者居家隔离导致以小区为单位的生鲜物资需求激增，而复工不足导致生鲜企业配送能力有限，生鲜物资运输受到更多挑战。基于生鲜企业配送时间限制，考虑生鲜物资的保存时间与防疫用品的防护时间，以消费者所在小区为需求点，构建疫情背景下生鲜物资运输路径优化模型，并根据模型设计了一种遗传算法进行快速求解，在完成配送任务的前提下，得到最优运输方案，最小化企业配送成本。同时，分析了不同需求情况下所需车辆数的变化，计算结果表明所需车辆数并未随需求同倍增加。

Study on the optimization of transportation path of fresh materials under COVID-19 epidemic

Under the background of COVID-19 epidemic, the domestic quarantine policy has led to a surge in demand for fresh supplies in the community. The insufficiency of resuming work has led to the limited distribution capacity of fresh food enterprises, and the transportation of fresh materials has faced more challenges. Based on the distribution time limit of fresh food enterprises, considering the preservation time of fresh supplies and the protection time of epidemic prevention supplies, this paper takes the community where consumers are located as the demand point and builds up an optimization model for the transportation path of fresh supplies under the background of pandemic. According to the model, a genetic algorithm is designed to solve the problem quickly. On the premise of completing the distribution task, an optimal transportation plan is obtained so as to minimize the enterprise's distribution cost. At the same time, changes of the number of vehicles required under different demand conditions are analyzed and it is shown that the number of vehicles required does not increase with the demand.