Logistics Transportation Routing Research About Agricultural Products Based On Improved Genetic Algorithm

With the development of economy and consumption level,the demand for agricultural products from companies and individuals is increasing and the demand for the logistics distribution level of agricultural products is also increasing.This has also brought great opportunities and challenges to China's logistics distribution of agricultural products.Opportunities are mainly reflected in the fact that the country has put forward the concept of “Internet+”and its high degree of emphasis.The integration of the Internet and agricultural product distribution has promoted the rapid development of China's agricultural product logistics industry.However,along with the development,the challenge of logistics distribution of agricultural products began to appear.First of all,meeting the customer demand and time window constraints in the agricultural product logistics distribution system is an important indicator to measure the service level of agricultural product logistics distribution.Secondly,for the perishable nature of agricultural products,it is required that the delivery party must be able to save time and cost for the entire distribution process while satisfying the requirements of individual customers in the actual delivery process.Finally,this article needs to choose an appropriate and efficient method after establishing the logistics distribution path model of agricultural products to solve the optimal selection of agricultural product distribution route.This is also an important factor for the success of agricultural product logistics distribution.This article analyzes and elaborates the basic theory of agricultural products,agricultural product logistics distribution and genetic algorithms by reading a large amount of domestic and foreign data.Then based on its theory,the logistics distribution model and genetic algorithm of agricultural products are optimized.Finally,aiming at the characteristics of agricultural product logistics distribution model,this paper improves the traditional genetic algorithm.In the process of designing an improved genetic algorithm,this paper first selects the integer coding in the coding so that each chromosome contains both the customer point and the path information.Then this paper proposes a method that can reduce the probability of infeasible solutions when the population is initialized.Finally,this paper improves the selection,crossover and mutation in genetic algorithms.This article uses the data from the Solomon database that is often used by the academic community to study path optimization problems,and combines the agricultural product logistics distribution models studied in this paper,adding missing data to these data.The validity and rationality of the improved genetic algorithm in this paper are verified.