| With the progress and development of China’s society and the continuous improvement of the people’s living standards,the market demand for fresh products continues to increase,and the scale of China’s fresh products market will continue to grow in the next few years.However,fresh products are perishable and vulnerable,and the distribution of fresh products has more stringent distribution requirements than general logistics products.How to optimize the logistics distribution path of fresh products,save distribution costs,increase customer satisfaction and logistics enterprise income has become a hot issue of current research.At the same time,customers’ demands tend to be dynamic and diversified in the distribution process.In the process of vehicle delivery tasks,there may be new customer demand points or changes in the planned distribution volume of the original customers.The dynamic variability of the distribution process is a research hotspot in the field of fresh product distribution.This paper studies the daily distribution process of J enterprise for chain supermarket and fresh food market,and summarizes the problems of J enterprise’s current distribution process such as high cost,low customer service level and high cost of goods damage in transportation,based on which,a multi-objective fresh product distribution model considering comprehensive cost and customer satisfaction is proposed.According to the characteristics of fresh products,this paper considers the loss cost,dispatching cost,variable cost,refrigeration cost and time penalty cost in the transportation process of fresh products.For the measurement of customer satisfaction in distribution,this paper establishes different time sensitivity parameter values through different customer types,and makes a double time window treatment of customer satisfaction function to better fit the actual distribution situation.For the static problem of fresh product distribution in J enterprise,this paper designs an improved multiobjective particle swarm optimization algorithm MOGAPSO based on the genetic algorithm GA,which effectively improves the global search ability,population richness and convergence accuracy of the algorithm.For the dynamic problem of fresh product distribution in J enterprise,a method of updating customer demand in batches at fixed time is designed,and the static initial solution is updated by inserting demand in different periods,which effectively solves the problem of dynamic customers and dynamic changes of customer demand in the process of vehicle distribution.Finally,based on the actual distribution data of Enterprise J on a certain day,this paper carries out simulation analysis with a specific example of Enterprise J’s distribution,and applies the improved algorithm to the solution of the multi-objective model in the static distribution environment of enterprises,and compares it with the non-dominated sorting genetic algorithm NSGA-II and the multi-objective particle swarm optimization algorithm MOPSO.The performance improvement of the improved MOGAPSO algorithm is verified by comparison,and a variety of different customer satisfaction schemes are provided for enterprises according to the distribution data of the day.In the dynamic environment,considering the change of vehicle speed,this paper uses the insertion method to improve the initial solution obtained by the static algorithm to solve the problem of new demand and the change of original demand in the distribution process of enterprises.Finally,the dynamic update strategy and the distribution cost without the strategy are compared and analyzed,which proves that the dynamic strategy can effectively improve the distribution process of fresh products.This paper,combined with the simulation data,provides a reference for the formulation of the fresh product distribution plan of J Enterprise. |
PDF Full Text Request