Research On Multi-range Multi-class Fare Seat Management Model Based On Particle Swarm Optimization

Along with the development of economy and technology, the number of serviceindustry revenue management research which based on the RM theory is growing dayby day. Domestic research still focuses on the introduction of foreign revenuemanagement theory and the promotion of different industries. Meanwhile, China'srailway passenger seat management and price system still uses the old method of theplanned economy period, which means railway bureau makes the amount of ticketdistribution plan according to historical data and forecast data of the traffic sections.This single-fare system and seat management system had seriously affected thedistribution of income and long-term development of railway.Based on the collection of literatures and books, firstly, paper introduced theconcept and the industry application characteristics of revenue management, based onthe elaborate of four mains components of revenue management: forecasting, pricing,seat management and overbooking, paper pointed out the basic process of revenuemanagement. Secondly, based on the analysis of two kinds of basic revenuemanagement models, paper considered the actual dissatisfied attitude of the passengerswho buy the full price ticket, added the penalty function which based on customersatisfaction, built a range of multi-range multi-class fare seat managementoptimization model. Finally, paper introduced the principle of particle swarmoptimization and the process based on PSO-based multi-range multi-class fare seatcontrol model design, and then based on the analysis of numerical results of the modelprosose the application in the pailway passenger, paper studied examples to verify thevalidity of the model.Through the model analysis and case studies, the results of the research can bedrawn as follows: added seat satisfaction penalty factor for the multi-range multi-classfare control model, enriched seat management model and deepened the understandingof the problem of seat management; By PSO improvement design and simulationmodel examples we can come to optimize distribution of seats, confirmed thesignificant effect of the model in the total income increase and the rational allocationof seats.