Distribution Routing Optimization On Fresh Produce

With the improvement of living standards, there is a increasing emphasis on healthy lifestyles, the demand for fresh and high-quality fresh produce is growing, but the traditional way to buy high-quality fresh produce channels have been unable to meet the diverse needs of customers. In recent years, e-commerce business model which is in a flexible and rapid response of consumers’ demand for personalized, quickly get the attention of consumers and businesses, but also provides a platform for the fresh produce about online promotion and trade. However, our currently e-commerce businesses in the the fresh business model is still in the exploratory stage, the distribution service is not mature, the distribution costs tends to be high and low efficiency, service levels are often difficult to guarantee.In order to reduce distribution costs and improve the efficiency of distribution, and to ensure the fresh distribution of e-commerce businesses complete smoothly and efficiently,the article tries to optimize the distribution route for the e-commerce businesses in the fresh. Firstly, the paper make the e-commerce businesses of fresh produce distribution networks compared with the traditional, described the e-commerce businesses of fresh produce distribution patterns, and discussed the problems of distribution of fresh produce. Then considered the factors which the delivery route optimization based on, such as time windows, repeated use of delivery vehicles, the travel time of fresh distribution, etc. And it established a route optimization model, which can ensure the freshness of fresh products, make full use of the vehicle and make the distribution costs minimal delivery. Finally, by way of Python programming, using hybrid genetic algorithm and substituting instances of Xianmatou, we get the lowest optimal for fresh agricultural city distribution costs, and vehicle travel scheduling scheme. The optimized routes compared to the original, it reduces delivery vehicles, so that cut the fixed costs; it reduces driving distance, so that variable costs also decreased; it sharps decline in transit latency and the efficiency of distribution increase. The optimization will increase the distribution of profits. In a word, the results of the optimization prove the model and the effectiveness of the algorithm.