Research On Multi-objective Model Optimization Of Cold Storage Multi-temperature Joint Delivery Under Dynamic Demand

The ever-changing science and technology has promoted the development of the economy and improved the living standard.Consumers have more and more demand for different types of fresh-layer fresh products,and the circulation multi-temperature products promotes the generation of cold storage multi-temperature joint delivery.However,China's cold storage multi-temperature joint delivery started late,the application range is still not widespread,and the logistics distribution cost is high,so there is great potential in saving logistics costs.In addition,in the process of delivery,the customer's needs will change at any time.When the customer arrives at the customer's point and the customer generates new demand,if the forecasting reserve is not made in advance,the customer's uncertainty about the cold chain product will not be satisfied.Demand,which reduces customer satisfaction.Therefore,how to quickly and accurately respond to customer dynamic changes in demand and provide timely and satisfactory delivery services to customers has become an urgent problem to be solved in a cold storage multi-temperature co-location system.This paper first analyzes the literatures on the vehicle routing problem and customer satisfaction of cold storage multi-temperature co-allocation and dynamic demand at home and abroad,and summarizes the current status and shortcomings of the research.Then it expounds the theoretical basis related to the research,including the conceptual characteristics and operation mechanism of the cold storage multi-temperature co-equipment,the principle and method of demand forecasting,the choice of the prediction method of this research,the basic concept of customer satisfaction and the analysis of influencing factors.On this basis,a multi-objective model of cold storage multi-temperature co-coordination and a prediction model based on exponential smoothing method are proposed.One of the objectives of the former is distribution cost-transportation cost,cargo damage cost and cooling cost,wherein transportation cost includes fixed cost.(Use cost of distribution vehicles and cold storage incubators),variable cost,and another goal is customer satisfaction.This paper considers the perishable nature of cold chain products based on the existing literature analysis on customer satisfaction.Uncertainty in characteristics and customer needs,measuring customer satisfaction from three dimensions:time satisfaction,cold chain freshness and order completion rate.This is one of the innovations of this paper;the latter is in response to customer dynamics.Demand,the prediction of dynamic demand is integrated into the distribution plan,and the exponential smoothing prediction model suitable for short-term forecasting and high precision is selected to solve the distribution ratio of different wamm-up goods in this distribution,making full use of the redundant space of the delivery vehicle.Carrying goods for many loads.In this paper,a genetic algorithm is used to solve a specific example,and the realization process of the cold storage multi-temperature co-property multi-objective optimization model under the dynamic demand established in this paper is expounded.It takes time to consider the demand forecast and not consider the demand forecast and consider the demand forecast.The full load and the full load of the remaining space,and the difference in the assembly ratio between different delivery vehicles when considering the demand forecast,compare the logistics cost and customer satisfaction of the two optimal distribution schemes.The research results show that the demand forecasting distribution scheme used in this paper has lost a small amount of cost,but it has brought about a significant increase in customer satisfaction.The differential processing strategy adopted in this paper for the ratio of redundant space allocation of different vehicles is better than the previous research prediction accuracy.Higher,the redundant space can be saved according to the proportion of the vehicle load occupied by the redundant space,which can save a lot of logistics costs compared with the full load of the existing literature.In suimnary,this paper analyzes and studies the cold storage multi-temperature co-property multi-objective optimization model under dynamic demand,which has important theoretical and practical significance.Theoretically,the research of this paper starts from the perspective of improving customer satisfaction,and the optimization of the model of cold storage multi-temperature co-cooperation helps to enrich the relevant theory of cold storage multi-temperature co-coupling.Secondly,the customer demand is considered in the model.The change,the exponential smoothing method is used to reasonably predict the redundant space of the distribution vehicle,to meet the customer's uncertainty requirements to the maximum,and enrich the dynamic cold chain logistics theory.In practice,in the context of the industry of cold chain logistics distribution system gradually changing from the traditional single-product temperature multi-vehicle distribution to the cold storage multi-temperature co-location system,the research in this paper aims to "reduce the cost of logistics distribution and improve customer satisfaction"."The practice and development of fresh-chain cold-chain logistics distribution enterprises for survival strategy has important reference value,and has great guiding value for the formulation of assembly schemes for logistics distribution enterprises with dynamic demand characteristics.