Optimization Of Multi-objective Cold Chain Logistics Distribution Vehicle Path Considering Customer Rating Classification

With the rapid development of the national economy,the people's pursuit of quality of life is also getting higher and higher.With the continuous development of Internet technology,the people's consumption patterns have also undergone great changes.The consumption structure of cold and fresh products has also changed,not only the demand for cold and fresh products has increased,but also the quality of cold and fresh products has become higher and higher.In order to improve their own market competitiveness,cold and fresh product sellers have put forward higher requirements for cold chain logistics distributors,especially to meet the delivery time and delivery quality requirements of different customers.For distributors,when the distribution of cold and fresh products is large and scattered,and the time requirements are high,the distribution resources are limited,and often all the requirements of the distribution customers cannot be met at the same time.Therefore,under the distribution resources of the distributor(vehicle,delivery personnel)is limited,consider the distribution customer value level,reasonably plan the vehicle path of the cold chain logistics distribution to improve the overall satisfaction of the distribution customer.At the same time reduce the distribution cost and increase the income.It has important reference value for companies.The contents and conclusions including:(1)Introduces the related theories of vehicle routing.cold chain logistics and customer value segmentation.According to the relevant characteristics of cold chain logistics distribution customers,the distribution customer value evaluation index system is constructed.Aiming at the ambiguity of the scope of distribution customer value evaluation,the cross-quantitative evaluation standard cloud model was introduced,and the multi-level fuzzy evaluation method based on cloud model was applied to classify customer value.By comparing with the fuzzy hierarchy method,the paper introduces the cloud model instead of the original membership function to overcome the single subjectivity of the membership function in the fuzzy evaluation process,and better reflect the randomness and ambiguity of the qualitative index of the evaluation index.This method can classify the value of the distribution customer effectively and accurately.(2)Describe the vehicle routing problem of cold chain logistics distribution considering customer value and delivery time sensitivity,classify customer distribution priority according to the sensitivity of distribution customer value level and time,set different time window constraint bars;then introduce transportation in detail The cost of the route,considering the calculation of penalty losses for customer rankings and the measurement of overall customer satisfaction,builds the model.This paper applies the main target method of multi-objective programming method to determine the distribution cost as the main goal.The customer's overall satisfaction T is a constraint condition,and the multi-objective planning is transformed into a single-objective plan,which is solved by genetic algorithm.Through the example calculation,it is found that the T value is from 85% to 95%,the total cost of distribution increases by about 6%,and the increase from 95% to 100% reaches more than 20%.The higher the satisfaction,the more the input costs.And as the satisfaction gets closer to 100%,the increase in the cost of input increases.(3)In order to verify the difference between considering customer value and time sensitivity classification and not considering customer value classification,the path is solved by setting different customer time window constraints.In contrast,the customer's value classification and time sensitivity are considered to be very small compared to the unconsidered distribution cost,but the VIP and time-sensitive customers can deliver at the expected time.Considering the path planning of customer value,customers in this category cannot guarantee delivery in the desired time window.It can be seen that the model finds the optimal path plan with the lowest total cost of distribution,customer time window and customer value,so that time-sensitive and high-value customers are delivered at the expected time,and the satisfaction is 100%.and verify that models and algorithms are Effective.