Research On The Pickup Route Optimization Of Fresh Agricultural Product Considering Demand-splitting

With the in-depth advancement of the rural revitalization strategy of China,the problem of agricultural products entering the city has attracted wide attention.In remote mountainous areas,fresh agricultural products have begun to industrialization,become the economic pillar of farmers,and have a very wide range of urban consumption demand.In order to make agricultural products in remote mountainous areas go to the dining table of consumers with accurate and fast logistics,realize good quality of products,fast transportation speed and high economic benefit of participants,the efficiency of front-end collection link is very important.However,affected by various factors,the development of front-end agricultural product collection lags behind,which seriously affects the supply and demand matching of fresh products between urban and rural areas.Based on the current policy environment,this paper studies the optimization of the.collection path from the first kilometer of agricultural products circulation,which has good practical significance.This thesis analyzes the current situation and characteristics of fresh agricultural products in remote rural areas,and studies the current front-end pickup mode of fresh agricultural products in rural areas.At the same time,considering the fact that logistics companies cannot develop the rural market without government subsidies and the products collected at a single station may exceed the vehicle weight limit,based on the in-depth analysis of fuel consumption,refrigeration,cargo damage and time penalty costs when the vehicle is empty and loaded as well as the government subsidies,a route optimization model of agricultural products considering demand splitting is constructed according to the current situation.Considering the fullload demand splitting on the basis of the traditional demand splitting problem,a demand splitting model considering only the splitting of full-load demands and one considering random demand splitting after full-load splitting are established aiming at maximizing the pickup profit of the products.Taking the pickup of navel oranges in Shuimiao Town,Xinning County,Shaoyang City as a case background,the feasibility of the front-end pickup of navel oranges is analyzed.According to the designed genetic algorithm,MATLAB programming is used to solve the problem.The results show that using the genetic algorithm with improved selection strategy,the obtained optimal route is reasonable,which can significantly improve the revenue and reduce the cost.The results of the model with random splitting after full-load splitting are generally better than that of the model in which only full-load splitting is considered.The pickup income reaches 195,971 yuan,800 more than that obtained by the first model.The average loading rate of each route increases from 79.6%to 85.7%,and the transportation mileage and other costs also reduce to a small extent,which means the vehicle loading rate is improved and the pickup revenue is increased while all the cargo collection needs of customers are satisfied.The research on the route optimization problem considering demand splitting provides a certain reference for Shuimiao Town to regulate the current front-end logistics chaos of navel oranges,to realize the rational allocation of rural logistics resources in Shuimiao Town,and to plan the route of agricultural products pichup vehicles.