CAJ | 학술논문

文章提出了一种基于遗传算法的铁路三维空间智能选线方法。建立铁路三维空间信息模型，为指定区域内铁路空间线位的智能搜索提供了基础信息条件；以铁路空间线位几何参数作为设计变量，充分考虑线路几何约束与环境影响约束作用，建立以最小综合代价为目标函数的多目标数学优化模型；应用基因浮点编码方式，提出以交点偏移距、链式变坡点标高作为基因的三维空间编码方法，设计了适应于铁路三维空间线形整体优化的遗传算子，对三维空间线路进行全局搜索与多目标寻优，合理控制线路方案的取舍，保持线路方案群的多样性。基于本研究所提出的理论和方法，开发了铁路三维空间智能选线系统，测试结果表明，搜索出的线路方案经济合理，验证了铁路三维空间智能优化算法的合理性与实用性。
문장제출료일충기우유전산법적철로삼유공간지능선선방법。건립철로삼유공간신식모형，위지정구역내철로공간선위적지능수색제공료기출신식조건；이철로공간선위궤하삼수작위설계변량，충분고필선로궤하약속여배경영향약속작용，건립이최소종합대개위목표함수적다목표수학우화모형；응용기인부점편마방식，제출이교점편이거、련식변파점표고작위기인적삼유공간편마방법，설계료괄응우철로삼유공간선형정체우화적유전산자，대삼유공간선로진행전국수색여다목표심우，합리공제선로방안적취사，보지선로방안군적다양성。기우본연구소제출적이론화방법，개발료철로삼유공간지능선선계통，측시결과표명，수색출적선로방안경제합리，험증료철로삼유공간지능우화산법적합이성여실용성。
A three-dimensional spatial intelligent approach for railway alignment optimization was developed,which is based on genetic algorithms.The 3 D spatial information model for railway alignment was built to provide basic informa-tion in assigned region for intelligent searching of the railway spatial alignment.The geometric parameters of railway spa-tial alignment were taken as the design variables,and the geometric constraint and environmental impact constraint of railway line were fully considered for establishment of the multi-objetive mathematical optimization model,with the mini-mum integrate-cost of railway as the objective.A genetic real encoding method was devised,which took the cutting dis-tance of intersection point and the elevation of chain-linked fold lines as its gene series.The genetic operator which a-dapted to the whole optimization of the railway spatial alignment was designed.The global search and multi-objective op-timization for the railway three-dimensional spatial alignment were conducted,controlling the choices of line scheme rea-sonably and maintaining the diversity of the scenarios.Based on the theories and methodology reviewed in this paper,a three-dimensional spatial intelligent route selection system was developed and had been widely applied to many railway projects.The scenarios also showed that the railway scheme searched was economic and reasonable,and that the ration-ality and practicability of the 3D spatial intelligent optimization algorithm was verified.