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The Bus Optimization Scheduling Of Intelligent Algorithm Based On State Space Model

Posted on:2016-07-27Degree:MasterType:Thesis
Country:ChinaCandidate:X LiFull Text:PDF
GTID:2322330488981894Subject:Control theory and control engineering
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With the rapid advance of urbanization process in our country, vehicle ownership sharply increased. But the city's comprehensive service ability and the efficient of infrastructure's construction do not match for the growth rate of car ownership. It leads to the road traffic tension and influences the urban sustainable development directly. So develop urban traffic system has become an urgent matter. Bus scheduling system is one of the subsystems of traffic system, it through the reasonable allocation of manpower and material resources to realize the optimization of bus scheduling and management. Because the bus optimization scheduling can bring good economic and social benefit, the domestic and foreign scholars has proposed many optimization methods to solve this problem.Public transportation optimization scheduling problem belongs to multi-objective and multi-constrained optimization problems, and have both hardness in modeling and solving, so this problem has not obtained a good solution and the study of this problem is still on going.Intelligent optimization algorithm based on state space model(SIA) was presented to solve bus scheduling problem, SIA adopted real number encoding and the basic idea of genetic algorithm(GA) was introduced to it. The state evolution matrix of SIA was used to solving the next generation group. The calculation pattern of traditional genetic algorithm was break through, the calculation process could be expressed by dynamics process of discrete system,then through the selection mechanism of selection pool to approached optimal solution. This algorithm is simple, and its optimization effect is good.In this thesis, through considering the departure time interval, bus company earnings and utilization constraint conditions, the mathematical model of balancing profit of bus companies and passengers was presented. This model through weight coefficient to reflects the interest tendency. SIA was applied to the design of bus optimization scheduling problem,with the help of simulation platform, through the example comparison, the effectiveness of SIA was verified.
Keywords/Search Tags:bus scheduling, intelligent optimization algorithm, genetic algorithm, state space model, State evolution matrix
PDF Full Text Request
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