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Research on the Marshalling-scheduling Model and Algorithms of Freight Trains Based on Game Theory
Author: YanMing
Tutor: LiuHongYan
School: Liaoning University of Science and Technology
Course: Applied Computer Technology
Keywords: Game Theory GMAIM Grouping scheduling Optimization Model Genetic Algorithms Marshalling yard
CLC: O225
Type: Master's thesis
Year: 2010
Downloads: 24
Quote: 1
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Abstract
With the rapid development of China 's railway modernization , the the station grouping scheduling efficiency bottleneck prominent. Complex problems , as a typical combination optimization freight train marshalling scheduling optimization become important research in the field of theoretical level and the practical application of significance . This article describes the achievements and shortcomings of the present stage of Railway Information , domestic and international scheduled freight train formation model and algorithm research status . The Agent of MAS related concepts , nature and application basics . Analysis of several classical optimization theory method . The development of game theory , by type , form and algorithm implementation platform . As a prototype, further research applied to the marshalling scheduling problem to GMAIM Agent game collaboration , establish the truck marshalling scheduling game conceptual model and design the corresponding game algorithm . Lorry marshalling workflow scheduling based on the nature and characteristics of the freight train the marshalling scheduling process , analysis , efficiency evaluation , optimization goals and constraints , established a solvable model freight the train marshalling scheduling optimization based on game theory . This article compares a variety of commonly used system job scheduling algorithm . A greedy algorithm for the marshalling scheduling model grouping scheduling algorithm , based on the operating method , network optimization with flow table grouping scheduling genetic algorithm . The authors studied the based FCFS the truck marshalling scheduling algorithm to achieve . A marshalling yard for calculation examples , algorithms optimized for 3 - class grouping scheduling algorithm efficiency comparison and analysis when the ceiling full of axle ratios , and other factors impact on the the marshalling scheduling efficiency . Finally , the authors analyze the relevant factors affect the marshalling yard disintegration ability . In reference to the basis of the existing research on the establishment of a marshalling yard through capacity calculation model , targeted research marshalling yard of the number of devices and load optimization strategy . Marshalling yard to the solution process simulation data , set up a series of initial simulation conditions , the process of marshalling yard for job repeatedly simulation .
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CLC: > Mathematical sciences and chemical > Mathematics > Operations Research > Game theory ( game theory )
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