Affiliation:
1. School of Management Science and Engineering University of Jinan Jinan China
2. School of Management Shandong University Jinan China
3. School of Mathematics and Statistics Shandong Normal University Jinan China
4. School of Finance and Economics Qingdao Binhai University Qingdao Shandong China
Abstract
AbstractIn recent years, the community group buying market has been developing rapidly, and the group buying categories are mainly fresh food, so one of the keys to the success of the community group buying platform lies in the supply chain logistics, in which the cold chain logistics is the key to guarantee the fresh food products for the time and quality. In this paper, on the combing research of the theories and problems of community group purchase, cold chain logistics, and vehicle path planning, in view of the existing problems of cold chain logistics and distribution business in Jinan distribution center of J company's community group purchase, taking into account the actual demand of the grid station and the characteristics of the fresh products to be stored at low temperatures, we constructed the optimization model of the cold chain logistics and distribution path that minimizes the total cost under the demand of the fuzzy time window of the grid station, and designed the distribution area is divided by using K‐means clustering, and then, the distribution path in each sub‐distribution area is optimized and solved by genetic algorithm, and then, the validity of the optimization scheme is verified, the number of distribution trucks used is reduced by two, and the distribution cost is reduced by 12.77%, and optimization measures such as promoting the standardization of warehousing and distribution, and creating a digital and integrated logistics information platform are proposed.
Funder
National Social Science Fund of China
Natural Science Foundation of Shandong Province
China Postdoctoral Science Foundation
Helsingin Yliopiston Tiedesäätiö