Research On Demand Forecast And Path Planning Of Agricultural Products

In recent years,with the country’s strong support for cold chain logistics,the cold chain logistics industry as a whole is developing toward standardization and consumers have higher and higher requirements for products.The demand market for cold chain logistics is growing rapidly.More and more market players are invested in the construction of cold chain logistics,which promotes the rapid development of cold chain logistics.However,due to the late development of cold chain logistics,cold chain logistics still lags behind developed countries in terms of cold chain infrastructure and standards.Cold chain logistics market demand growth does not match the cold chain supply.At the same time,the green and low-carbon economy and the fierce market competition environment,green development and customer satisfaction for the development of cold chain enterprises become more and more important.Based on this,this thesis takes cold chain logistics of agricultural products as the research object,focuses on the optimization of cold chain logistics demand and distribution route of agricultural products,provides theoretical and practical guidance for the development of cold chain logistics industry of agricultural products,and promotes the development of cold chain logistics of agricultural products to high quality.This thesis intends to use literature review method,combination prediction method,improved genetic algorithm,data mining and modeling method,case analysis method,etc.,through the establishment of combination prediction model to predict and analyze the demand of cold chain logistics of agricultural products in Chongqing,so as to achieve the optimal distribution of cold chain logistics of agricultural products.First of all,in order to more accurately grasp the demand situation of Chongqing agricultural cold chain logistics,this thesis intends to use two models of principal component regression and BP neural network,and use Shapley value method for weight distribution to get a combined prediction model,and comparative analysis,and finally analyze the demand trend of Chongqing agricultural cold chain logistics with the combined prediction model.Secondly,taking Chongqing as an example,through the demand analysis of cold chain transport of agricultural products,the development path of cold chain transport of agricultural products was studied.Considering customer satisfaction,load and other indicators,an optimization model aiming at the lowest total cost was established.Finally,for the model problem,the elite strategy optimization genetic algorithm is introduced,and the improved and basic genetic algorithms are respectively used to solve the problem,and the efficiency is verified by comparative analysisThe results show that: first,compared with the single prediction model,the combined model of principal component regression prediction model and BP neural network prediction model is more accurate and more suitable for the analysis of demand problems.Secondly,compared with the basic genetic algorithm,the improved genetic algorithm can solve the model with better effect and lower total cost,which verifies the correctness of the model and the effectiveness of the algorithm.Thirdly,through the analysis of the demand of cold chain logistics of agricultural products in Chongqing and the study of the distribution route,the suggestions for the development of cold chain logistics of agricultural products have certain reference value for the government and enterprises.