Modeling and Solving Real-Time Logistics VRP Based on Markov Process
To effectively improve the service quality and reduce the total transportation time under the circumstances of stochastic traffic flow,this paper introduces two indicators of satisfaction and traffic flow,and constructs a logistics service problem model that weighs the total transportation time and service penalty cost based on the Markov process.In view of the complexity of the problem,a hybrid genetic algorithm is proposed to solve it in this paper.For the proposed hybrid algorithm,the local search strategy based on Service Quality Improving(SQI)takes into account the total vehicle transportation time and customer satisfaction,so that the algorithm can search in effective space.In order to verify the effectiveness of the model and algorithm,this paper conducted experiments on 56 test examples of the Solomon data set.The results show that the proposed hybrid genetic algorithm achieves 100％satisfaction evaluation on 28 samples in terms of sample optimization service quality.Compared with the standard genetic algorithm,it has increased by 29％while achieving the goal of the lowest total cost.
万方数据
维普
