Research On Optimization Of Cold Chain Logistics Distribution Path Under Uncertain Demand

With the development of the economy and the improvement of people's living standards,consumers demand for cold chain products is increasing,and at the same time,they put forward higher requirements on the level of cold chain logistics services provided by enterprises,which promotes the continuous development of cold chain logistics and also gives enterprises Bring various challenges such as cost and service.At present,there are still many problems to be solved in cold chain logistics.For example,unreasonable distribution path planning results in excessive distribution costs,or poor distribution service quality leads to low customer satisfaction.These problems restrict the further development of cold chain logistics.development of.The vehicle distribution link is a key link in modern cold chain logistics.Taking into account the random demand at the demand point,it is important for the enterprise to reasonably plan the cold chain logistics distribution path,thereby.reducing the company's distribution costs and improving customer satisfaction.Reference value.This paper studies the optimization problem of cold chain logistics distribution routes under uncertain demand,builds models and designs algorithms to solve them.The main research work and research results are as follows:(1)First,elaborate on the current status of relevant research at home and abroad,and consult relevant books and documents based on the research content of this article,summarize the basic theory of cold chain logistics and vehicle routing problems,and introduce the relevant algorithms for solving vehicle routing problems in detail.(2)Based on theories such as cold chain logistics and vehicle routing problems,describe the cold chain logistics distribution routing problem under uncertain demand,clarify the calculation method of various costs in the cold chain logistics distribution process,and comprehensively consider the refrigerated truck Fixed costs,transportation costs,cargo damage costs,cooling costs,and penalty costs under the mixed time window,and at the same time,according to the actual customer demand uncertainty that may occur in the actual distribution,when the customer's needs are not met,there will be out-of-stock costs,thus Build an optimization model that minimizes total cost and maximizes customer satisfaction.Apply the main objective method of the multi-objective planning method,determine the total distribution cost as the main objective,and transform the customer's overall satisfaction level into constraints,so that it can meet certain requirements,thereby transforming the multi-objective planning into single-objective planning.And design genetic algorithm to solve.(3)By analyzing the problems existing in a cold chain logistics enterprise in Dalian,collecting data and setting model parameters,applying the model constructed in this article to the actual situation,using Matlab software to solve the genetic algorithm programming and obtaining a satisfactory distribution path,Minimize distribution costs and ensure that customer satisfaction meets constraints,and finally verify the rationality and effectiveness of the models and algorithms constructed.