Model And QEA For Logistics Distribution Vehicle Routing Problem Of Low Carbon With Simultaneous Pickups And Deliveries

With the rapid development of modern logistics industry and people’s high attention to the problem of greenhouse effect, Considering the carbon emissions and the customer demand has become a hot research on vehicle routing problem now. Through designing the reasonable route to save the cost of enterprise and to reduce the carbon emissions, which has the important practical significance for increase enterprise competitiveness and curb global warming.In this paper, for several typical problems of vehicle routing problem of low carbon with simultaneous pickups and deliveries, analyzing the theory and the background of practice, three models are established. Multi-vehicle VRP, multi-depot VRP with multi-objective VRP, time dependent with multi-objective, and research the QEA for those problem, the main research work and achievements are as follows:Firstly, introduce the research background and significance, research the development status on the vehicle routing problem with simultaneous pickups and deliveries, and research the vehicle routing problem of low carbon. The research contents of this paper are based on these theories. Aiming at the existing problems, the main research content and organizational structure are proposed.Secondly, aiming at energy-saving for logistics, vehicles’ diversification and the customer has take and delivery requirements in the vehicle routing problem. A model for multi-vehicle routing problem of low carbon with simultaneous pickups and deliveries is established. The model put forward the calculation of considering the loading capacity, the models and the distance for carbon emissions. Base on the nature of the problem, using the Quantum Evolutionary algorithm to solve it. Finally, a numerical example test is used, experimental results show that the accuracy of the model and the effectiveness of the algorithm.Thirdly, using the strategy of making multiple distribution centers abstract into a distribution center, a model that multiple distribution centers for vehicle routing problem with simultaneous pickups and deliveries is established. The objective of the model is the minimal carbon emissions and the shortest route. The model uses the multi-objective QEA to solve the Pareto solutions. Finally, a numerical example test is used, experimental results show that the accuracy of the model and the effectiveness of the multi-objective QEA to solve the multi-objective problem.Fourthly, considering the customer has take delivery requirements and the time window constraints, According to the travel speed dependent function, a model for time dependent vehicle routing problem that is established. The objective of the model is the minimal carbon emissions and the shortest travel time. The model uses the multi-objective collaborative QEA algorithm to solve. Finally, through comparison and analysis of experiment, analyses the influence of the algorithm parameters, the population size and the number of iterations to the results. Experimental results show that the accuracy of the model and the effectiveness of the multi-objective collaborative QEA to solve the multi-objective problem.Fifthly, on the basis of the above-mentioned theory research, a simulation platform for vehicle routing problem of low carbon with simultaneous pickups and deliveries is made. The platform integrates the model and the quantum evolutionary algorithm from every chapter above, which verify the effectiveness of the proposed algorithm.