Research On Heterogeneous Fixed Fleet Vehicle Routing Problem Considering The Goods Type Of Customer Demand

With the rapid development of the world economy and the advancement of modern science and technology, logistics industry has gradually become the basic industry of the national economy and "the third profit source" of modern enterprise. And as core function of the logistics system, the quality and service levels of distribution have a direct impact on the cost of the entire logistics and customer service satisfaction. As one of the hot research topics in the field of modern logistics, Vehicle Routing Problems(VRP) aims to meet the customer requirements with optimal costs while deliver the goods to the destination at the same time, but traditional VRP only considers the cost, analysis of specific customer needs was not included in consideration.Based on the traditional cost-function model of Vehicle Routing Problems with Time Windows, this paper takes the goods type of customers demand into account, and a Heterogeneous Fixed Fleet Vehicle Routing Problem model whose objective function is composed of vehicle fixed cost, transportation cost and time penalties. Different type of goods have different time sensitivity and property, so requests for delivery time and transportation vehicles are not the same, so the deliver time and type of transport vehicle are different too. This model chooses the vehicle type for the customer and determines the coefficients of time penalties according to the goods type of customer demand. This helps with reducing costs while improving customer service quality, and it’s much closer to reality.A Genetic Algorithm is designed to solve the model build by this paper, which generates a good chromosome and add it to the original population of chromosomes according to the match constraint of the goods type of customer demand and vehicle type, and the time window constraint. The selection method is combined with optimal save strategy and proportion selection method to accelerate the convergence rate of the population. This paper uses three series of Solomon standard data to do the test, and the result shows the effectiveness and accuracy of this model and the algorithm designed.