Simulation of Long-Distance Logistics Distribution Scheduling in Response to Random Demand of Users
Generally,long-distance logistics involves multiple nodes,multiple transportation modes and different transportation paths,so we have to consider the time window requirements between different nodes.The difficulty of information transmission and coordination during the scheduling process will increase as a result.Therefore,a long-distance logistics distribution scheduling algorithm was proposed to respond to the random needs of users.Based on the user's random demand information and experience data,the reasonable occurrence probability of virtual users,co-ordinate position and demand information were obtained by aggregation and prediction.In order to achieve the shortest scheduling time and the highest user satisfaction in long-distance logistics distribution,a long-distance logistics dis-tribution scheduling model responding to users'random demand was built according to the principle that vehicles first deliver to real users before delivering to virtual users.Finally,an improved Particle Swarm Optimization(PSO)algo-rithm was introduced to solve the model.Thus,the optimal scheduling scheme was determined.Simulation analysis proves that the proposed algorithm can respond to user demand quickly,and user satisfaction is more than 96%all the time.The longest dispatching time of long-distance logistics is only 30min.
Respond to usersRandom demandLong-distance logisticsDelivery scheduling
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