摘要
重载铁路集疏运一体化的建立和实施,是铁路运输彻底摆脱计划经济、主动适应市场经济发展的有效途径。重载铁路是大能力运输通道,两个端点的工作效率和协同能力决定整个系统的成败,尤其是现有端点为多客户和多技术作业环节的情况下,协同的重要性可见一斑。集疏运一体化是集疏运系统协同的表现形式。集疏运一体化的协同运输组织模式能在相当程度上缓解货流不均衡、列车随机到达而导致的压车压货现象。集疏运系统在发展运行过程中通过协同合作,形成拉动效应,降低成本、提高效率。协同的结果使各主体获益,整体加强,共同发展。加强对重载铁路集疏运系统协同的研究,不仅对重载铁路集疏运系统的建设和运用具有指导意义,而且对既有铁路集疏运系统的建设有很强的借鉴作用,能优化铁路资源配置,显著提升铁路运输能力,对促进国民经济和社会发展具有深远的影响和意义。
本论文在铁道部重点项目《重载能力技术研究-大秦铁路货运组织运力配置辅助决策技术研究》的资助下,通过大量现场调研,在对重载铁路集疏运理论和实践进行总结分析的基础上,运用协同理论、运输组织理论等理论和方法对重载铁路集疏运系统协同的相关问题进行深入探讨,主要研究结论与创新点如下：
(1)对重载铁路集疏运系统协同从内涵、外延、内容、层次等四个方面进行了界定。内涵就是将集、疏、运三过程视为不可分割的整体,从整体作业效率和社会效益最大化出发,统一技术作业过程、统一编制集、疏、运计划,统一组织实施的组织模式。外延包括装备协同、技术协同以及能力协同三个方面。内容包含了基本要素、作业流程、信息技术、组织管理层面、文化层面、安全层面等六方面内容。层次包含了宏观、中观和微观三个层次。
(2)在1989年～2009年我国货运量及相关数据的基础上运用多元回归预测法、灰色预测法、指数外推法对2012～2016年我国铁路煤炭运输量进行预测,在此基础上运用变权重组合预测法模型对2012～2016年我国铁路煤炭运输量进行了预测精度更高的二次预测。预测结果表明铁路煤炭运输量会持续增加,需要铁路进一步提高煤炭运输能力。
(3)研究了重载铁路集疏运系统协同演化原理、环境条件和动因。重载铁路集疏运系统具备自组织发生的内、外部条件,系统要素的自组织活动是重载铁路集疏运系统实现协同的内因和决定性力量。运输效率作为序参量在重载铁路集疏运系统中取得支配地位,成为该系统内部的核心。实施集疏运一体化的协同运输组织模式,可以大大提高运输效率,因此系统发展、演化的结果就是采用集疏运一体化的协同组织模式。通过协同演化方程找到平衡点,集、疏、运三方均实现了参加协同后的效益优于不参加协同供应链时的效益。从经济、政策和技术三方面分析了重载铁路集疏运系统协同形成的环境条件。从自动力和他动力两个方面分析了重载铁路集疏运系统协同形成的动因。
(4)基于故障树和模糊随机Petri网对重载铁路集疏运系统协同的可靠性进行分析。对系统协同可靠性进行描述,分析了重载铁路集疏运系统的特点和可靠性模块,为方便研究对其理想化的假设和条件限定,用故障树和模糊随机Petri网对系统协同的可靠性进行分析。
(5)建立了重载铁路集、疏、运三个子系统协同指标,研究了集疏运系统协同状态评价方法。集、疏、运子系统的协同指标按固定设施、移动设备、人力资源和组织技术四类又分为数量指标和质量指标,确定功效系数评价法和隶属函数协调度判断法适用于重载铁路集疏运系统协同程度评价。
(6)对大秦铁路集疏运系统能力协同采用协同度模型进行分析。大秦铁路集疏运系统现阶段能力和2012年目标匹配为优良协同；集疏运系统整体协同度较低,仅为0.61；通道运输与疏运系统能力差距较小,协同度为0.8,属优质协同；集运系统中,装车点和集运线路协同度为0.91,属优质协同,湖东站和装车区的能力协同度仅为0.51,属基本不协同：集运系统与通道运输能力协同度为0.76,属基本协同,和疏运系统能力协同度为0.61,属轻度不协同。
(7)对大秦铁路集疏运系统协同可靠性采用了基于故障树和模糊随机Petri网的方法进行了分析,其协同可靠度为0.723625。在对λ和τ精确值分别取±10、±15和±20%模糊化作为其上下限时计算,系统可靠度分别为0.7218396、0.7201219、0.7166781,采用模糊随机Petri网方法分析可修系统可靠度是可行和有效的。
The construction and implementation of an integrative collection and distribution system of heavy haul railway is an effective way for railway transport to completely free itself from the planned economy and adapt to the market economy. The heavy haul railway is a large-capacity transport channel, but whether the whole system will be successful or not will be determined by the efficiency and synergy of the two endpoints of this channel. This is more evident in the case of that the existing endpoints are of a chain of operations featured by multi-client and multi-technology. The integrative collection and distribution system is a manifestation of the synergy organization of collecting and distributing. The cooperative transport organization mode of the integrative collection and distribution system can diminish the deposition of vehicles and cargo caused by imbalanced cargo flows and random train arrivals. During the development of the collection and distribution system, the synergic collaboration will form a pulling effect, reduce costs and improve efficiency, which will result in that all the subjects will benefit, the overall system will be strengthened and developed. To strengthen research on the synergy of the collection and distribution system of heavy haul railway, will not only provide guidance for the constriction and implementation of the collecting and distributing system of heavy haul railway, but also will offer a strong reference to the construction of the collection and distribution system of the existing railway. This kind of research will help optimize allocation of the railway resources and significantly improve the railway transport capacity, which will have far-reaching influence and significance to promote the state economic and social development.
With the funding of the project "Research on the heavy-haul capacity technology and the auxiliary support technology for freight organization in Daqin railway" and based on lots of site survey, this dissertation focuses on the in-depth study of the synergic problems in the collection and distribution system of heavy hall railway. In this dissertation research, the theories and methods of Synergetics and Transport Organization are used on the basis of summarizing and analyzing the theories and practices of the collection and distribution of heavy haul railway, and the main conclusions and innovative points are outlined as followings:
The connotation, extension, content, and hierarchy of the synergy of the collection and distribution system of heavy hall railway are defined. The connotation is that collection, evacuation and transportation are taken as an integrated entirety, in which it unifies the operating procedure, the integrated presentation of the collection, evacuation and transportation plan and the implemented organizational model aiming to maximize the overall operational efficiency and maximize the overall social benefits. The extension includes equipment coordination, technical cooperation and capacity collaboration. The content includes the basic elements, operational processes, information technology, organization management, culture and security. The hierarchy contains the macroscopic, medium and microscopic levels.
Different prediction methods, including the multiple regression prediction, the gray prediction and the extrapolation index, are used to predict the railway transportation volume of coal in china from2012to2016, based on the related data of railway freight volume from1989to2009in China. Moreover, this dissertation predicts China's railway transportation volume of coal from2012to2016more accurately by means of Weight-varying Combination of Forecast Models. The prediction results show that the railway transportation volume of coal will continue to increase and the railway transportation capacity needs to be further improved for coal transportation.
The principle, the environmental conditions and the driving forces of the synergic evolution of the collection and distribution system of heavy hall railway are studied. The collection and distribution system of heavy haul railway is satisfied with internal and external conditions to produce self-organization. The self-organizing activities of the system elements are the internal and decisive force for the collection and distribution system of heavy haul railway to achieve coordinated development. Transport efficiency as the order parameter gains a dominant position in the collection and distribution system of heavy haul railway and becomes the internal core of this system. The implementation of synergistic organization mode of the integrated collection and distribution will greatly improve the efficiency of transportation; therefore the result of development and evolution the system is the utilization of the synergistic organization mode of the integrated collection and distribution. The collaborative evolution equations are used to find a balance under which all the three parties of collection, evacuation and transportation in collaboration gain more benefits than not in collaborative supply chain. From economic, policy and technical perspectives, the environmental conditions for forming synergy in the collection and distribution system of heavy haul railway are analyzed. From the two aspects of self motivation and non-self motivation, the driving force of forming synergy in the collection and distribution system of heavy hall railway is analyzed
The reliability of the synergistic collection and distribution system of heavy haul railway is studied based on the fault tree and fuzzy stochastic Petri net. The collaborative reliability of the system is described, and the characteristics and reliability module of the collection and distribution system of heavy haul railway are analyzed. With the idealized assumptions and the limited conditions, the fault tree and fuzzy stochastic Petri net are used to analyze the reliability of synergies of the system.
The synergy index of the three subsystems of collection, distribution and transportation of heavy haul railway is established. The evaluation method of the synergistic collection and distribution system is studied. The synergy index is divided into quantity indicators and quality indicators. The membership function coordination judgment method adapts to the evaluation of synergy degree of the collection and distribution system of heavy haul railway.
The collaborative model is used to analyze the capacity of the collection and distribution system of Daqin railway. At current stage, the capacity of the collection and distribution system of Daqin railway exactly matches the target for the year of2012, which denotes the excellent collaboration. The collaboration of the collection and distribution system in its entirety is low, only with a value of0.61. The gap between the channel transport and the distribution system capacity is small, with a synergy degree of0.8, which denotes high-quality collaboration. In the collection system, the synergy degree of the loading point and the group lines is0.91, which denotes high-quality collaboration; but the synergy degree of the capability of the East Lake Station and the loading areas is only0.51, i.e. it is basically non-collaborative. The synergy degree of the capability of the collection system and the channel transportation is0.76, and it is a basic synergy. The synergy degree of the capability of the collection system and the distribution system is0.61, and it is a mild synergy.
The fault tree and the fuzzy stochastic Petri net are used to study the collaborative reliability of the collection and distribution system of Daqin railway. The collaborative reliability is0.723625. After a blurring calculation of±10,±15and±20%as their upper and lower to the precise value of λ and τ, the system reliability becomes0.7218396,0.7201219and0.7166781. This denotes that using the fuzzy stochastic Petri net to analyze the reliability of the fixable system is feasible and effective.
引文
[1]郭玉华.中国铁路货运营销理论与发展[D].长沙：中南大学,2011.
[2]张莹,杨建明.供应链协调与供应链协同内涵辨析[J].管理与财富,2009(3)：51-51.
[3]钱立新.国际铁路重载运输发展概况[J].铁道运输与经济,2002(12)：55-56.
[4]钱立新.世界铁路重载运输最新进展[J].铁道建筑,2007(8)：46-48.
[5]耿志修.大秦铁路重载运输技术[J].铁道知识,2009(3)：4-10.
[6][苏]帕里斯特,切列帕申涅茨.超重超长列车运行[M].北京：铁道出版社,1985.
[7]Van Der Merwe, J. H. Exploiting heavy haul experience. Railway Gazette International,1990, (9):671-674.
[8]Willem C Kuys. Ore Line Capacity Expansion:Conceptual Design of the Railway Line to Increase Capacity.9th International Heavy Haul Conference, vol2, Beijing, China:China Railway Publishing House,2009,941-949.
[9]Batisse. F. Heavy haul:a challenge or an opportunity for Europe's railways. Rail International.2003,34(9):18-31.
[10]Vieira, Paulo.Upgrading Form a CTC Into a CBTC System in a Dense Traffic Heavy-haul Railroad.9th International Heavy Haul Conference, vol2, Beijing, China: China Railway Publishing House,2009,760-768.
[11]Michael J.Hawthorne. LEADER'S Evolution to Train Control.9th International Heavy Haul Conference, vol2, Beijing, China:China Railway Publishing House, 2009,728-733.
[12]Michael. R. Total Friction Management on Canadian Pacific.9th International Heavy Haul Conference, Beijing:China Railway Publishing House,2009,2(9): 846-856.
[13]Konstantin P.Shenfeld. Studies and Measures to Provide WheelRail Performance of Heavy and Long Train Operation in the Russian Railways.9th International Heavy Haul Conference, Beijing, China:China Railway Publishing House, 2009,2(9),1005-1011.
[14]Shen. G. Dynamic effects, rail corrugations, and shakedown limits.9th International Heavy Haul Conference. Beijing, China:China Railway Publishing House.2009,2(9):796-800.
[15]张嘉通.试论发展我国重载列车的几个问题[J].铁道学报,1985,7(1)：57-65.
[16]韩宝明,刘其斌,胡锦云.维修“大窗”对电气化重载运输专线输送能力的影响[J].北方交通大学学报,1993,17(3)：256-264.
[17]李鹏,吴小强.基于遗传算法的重载与非重载去向开行方案比较研究[J].中国铁道科学,2000,21(3)：38-43.
[18]牛会想.提高大秦线能力研究[D].北京：北京交通大学硕士学位论文,2004.
[19]李进.大秦线实现年运量2亿吨扩能方案相关问题研究[D].北京：北京交通大学硕士学位论文,2004.
[20]梁倩.大秦线开行2万吨重载列车对湖东编组站到发场的影响[J].中国铁道科学,2005,26(3)：1-6.
[21]张述峰.万吨重载列车在湖东站二场占有到发线时间分析[J].铁道运输与经济,2005,27(12)：56-57.
[22]杨浩,夏胜利.大秦线实现年运量4亿吨的运输组织问题研究[A].中国科协2005年学术年会铁道分会场暨中国铁道学会学术年会和粤海通道运营管理学术研讨会论文集[C],2005.
[23]何冯斌.重载铁路运输装车区车流组织及相关问题研究[D].成都：西南交通大学硕士学位论文,2007.
[24]唐保刚.重载运输装车区车流组织的研究与探讨[D].北京：北京交通大学硕士学位论文,2009.
[25]马晓珂.重载运输组织方式及相关问题的研究[D].成都：西南交通大学,2006.
[26]郭楷.重载运输的通过能力研究[D].长沙：中南大学,2007.
[27]范正平.装车地直达重载运输[D].北京：北京交通大学,2006.
[28]陈锴.大连港集装箱集疏运系统规划研究[D].大连：大连海事大学,2002.
[29]张胜仙.龙口港集疏运系统优化研究[D].大连：大连交通大学,2008.
[30]刘铭.港口集疏运问题研究[J].现代商贸管理,2010,22(13)：126-127.
[31]黄芳.港口物流系统集疏运环节协调优化分析[D].成都：西南交通大学,2006.
[32]米晓晨.天津港集疏运系统规划研究[D].大连：大连海事大学,2006.
[33]韩建成.大连港铁一体化集疏运体系研究[J].中国铁路,2006(5)：65-67.
[34]尹传忠,李秀泉,卜雷.港口铁路集疏运系统规划研究[J].中国铁路,2010,(2)：67-69.
[35]孙光圻,孙宏.大连建设东北亚国际航运中心总体发展战略[M].大连：大连海事大学出版社,2005.
[36]吕靖,王杰.大连东北亚国际航运中心发展战略规划研究[M].大连：大连海事大学出版社,2005.
[37]张曙光.中国铁路运输组织理论创新与实践[M].北京：中国铁道出版社,2009.
[38]耿志修,大秦铁路重载运输技术[M].北京：中国铁道出版社,2009.
[39]冯芬玲,陈治亚,雷志鹏.铁路重载运输集疏运一体化协同学动因及实践[J].铁道运输与经济,2010,(8)：25-29.
[40]周孝文.大秦铁路集疏运通道能力分析与对策[J].铁道经济研究,2005(1)：35-37.
[41]王启铭.大秦线集运系统建设研究[J].太原铁道科技,2009(2)：8-11.
[42]林奋强,王德占,王耀球.加快推进集疏运系统建设的思考[J].铁道货运,2008(5)：17-19.
[43]傅选义.铁路集疏运系统规划建设的实践与探索[J].铁道运输与经济,2009(7)：1-5.
[44]张进川.半封闭式重载铁路运输组织关键技术研究[D].北京：北京交通大学,2008.
[45]武汛.大秦线运输组织系统研究[J].中国铁路,2009(6)：11-15.
[46]武汛.大胆创新勇于实践打造世界一流的大秦铁路重载煤运通道[J].中国铁路,2007(3)：5-8.
[47]SU Shunhu. The Research on the Organization Mode of Heavy-haul Transport of China Railway.9th International Heavy Haul Conference, Beijing, China:China Railway Publishing House,2009,2(9)955-961.
[48]刘博.重载列车组合站通过能力研究[D].北京：北京交通大学,2008.
[49]金玲.基于自组织理论的建筑业系统演化发展研究[D].哈尔滨：哈尔滨工业大学,2007.
[50]万向东,刘林平.世界体系论对发展中国家过度城市化的解释[J].求索,2001(6)：66-69.
[51]吴彤.自组织方法论研究[M].北京：清华大学出版社,2001.
[52]Haken. H. Information and Self-Organization [M]. New York:Springer-Verlag, 1998.
[53]许国志等.系统科学[M].上海；上海科技教育出版社,2000.
[54]许国志.系统科学[M].上海：上海科技教育出版社,2004.
[55]孙耀君.西方管理学名著提要[M].南昌：江西人民出版社,1998.
[56]席酉民,尚玉钒.和谐管理理论[M].北京：中国人民大学出版社,2002.
[57]匡敏,胡思继,邢培昱等.基于国民经济大系统下的铁路货物运输量预测方法的研究[J].北方交通大学学报：社会科学版,2003,2(14)：21-24.
[58]张喜.基于意向调查数据的非集计运量预测模型估计的研究[J].铁道学报,2000,22(2)：10-15.
[59]李红启,刘凯.基于分形理论的铁路货运量分析[J].铁道学报,2003,25(3)：19-23.
[60]朱子虎,翁振松,任民等.基于分形理论的铁路客货运量预测[J].铁道运输与经济,2011,33(7)：80-84.
[61]林晓言,陈有孝.基于灰色—马尔可夫链改进方法的铁路货运量预测研究[J].铁道学报,2005,27(3)：15-19.
[62]张诚,周湘峰.基于灰色预测—马尔可夫链—定性分析的铁路货运量预测[J].铁道学报,2007,29(5)：15-21.
[63]赵闯,刘凯,李电生.支持向量机在货运量预测中的应用研究[J].铁道学报,2004,26(4)：10-14.
[64]郝佳,李澜.铁路货运量组合预测模型的研究[J].铁道运输与经济,2004(11)：73-75.
[65]魏宗舒.概率论与数理统计教程[M].北京：高等教育出版社,1983：1-18.
[66]张金櫆.线性模型参数估计及其改进[M].长沙：国防科技大学出版社,1 999：18-26.
[67]唐年盛,王娅,罗贤奎.多元加权约束线性回归的影响分析[J].云南大学学报：自然科学版,2000,22(2)：92-94.
[68]农秀丽,刘万荣.非齐次等式约束线性回归模型参数的条件根方估计[J].重庆师范大学学报：自然科学版,2007,24(2)：24-28.
[69]Pawlak. Z. Rough set:theoretical aspects of reasoning about data. Dordrecht: Kluwer Academic Publishing,1991.
[70]张文修,吴伟志,梁吉业,李德玉.粗糙集理论与方法[M].北京：科学出版社,2001.
[71]王国胤.Rough集理论与知识获取[M].西安：西安交通大学出版社,2001.
[72]Pawlak. Z. Rough sets and decision analysis [J]. Institute for:Rough Sets and Web-Based Systems in Decision Support Processing.2000,38(3):132-144.
[73]Pawlak. Z. Rough sets [J]. International Journal of Information and Computer Science,1982, (11):341-356.
[74]韩祯祥,张琦,文福拴.粗糙集理论及其应用综述[J].控制理论与应用,1999,16(2)：153-157.
[75]钟波,肖智.一种基于粗糙集理论的组合预测方法[J].统计研究,2002(11)：37-39.
[76]邓聚龙.灰色系统理论教程[M].武汉：华中理工大学出版社,1990.
[77]邓聚龙.灰预测与灰决策[M].武汉：华中科技大学出版社,2000：43-140.
[78]谭冠军.GM(1,1)模型的背景值构造方法和应用[J].系统工程与理论实践,2001,21(5)：124-128.
[79]吕林正,吴文江.灰色模型GM(1,1)优化探讨[J].系统工程与理论实践,2001,(8)：92-96.
[80]吉培荣,黄巍松,胡翔勇.灰色预测模型的特性研究[M].系统工程与理论践,2001,(9)：103-108.
[81]张高峰,姜国辉,付永锋.灰色GM(1,N)自记忆模型研究[J].沈阳农业大学学报,2009,40(2)：210-214.
[82]王景等.组合预测方法的现状和发展[J].预测,1997,(6)：37-38.
[83]Bates J M, Granger C W J. Combination of forecasts[J]. Operational Research Quarterly,1969,20(4):451-468.
[84]Pawlak. Forecasting (Special Issues on Combination Forecasting),1989(3): 15-20.
[85]唐小我.最优组合预测方法及其应用[J].数量统计与管理,1995,11(3)：31-35.
[86]唐小我等.递归等权组合预测方法研究[J].电子科技大学学报,1992,21(5)：545-550.
[87]唐小我,曹长修.组合预测最优向量的进一步研究[J].预测,1994(3)：15-18.
[88]赵国忻,王明涛.一种变权重组合预测方法研究[J].西北纺织工学院学报,2000,14(3)：226-232.
[89]曾勇,唐小我.经济规划在非负权重最优组合预测计算中的应用[J].预测,1994(5)：26-32.
[90]曹长修,王景,唐小我.一种模糊变权重组合预测方法-FVW法的研究[J].预测,1996(5)：16-22.
[91]唐小我,王景,曹长修,一种新的模糊自适应变权重组合预测算法[J].电子科技大学学报,1997(3)：289-292.
[92]世界最繁忙铁路：大秦铁路年运量突破4.4亿吨.中国广播网(北京).2012-01-03.
[93]哈肯,高等协同学[M].郭治安.译.北京：科学出版社,1989.
[94]叶峻青,程碧荣.重载铁路集疏运一体化形成机理研究.2010 International Conference on Circuit and Signal Processing(ICCSP 2010). volume(2).2010.12.25.
[95]李士勇.模糊控制·神经控制和智能职能控制论[M].哈尔滨工业大学出版社,129-135.
[96]王显政.中国能源高层对话暨新版“新华网能源频道”发布仪式的讲话[R].北京：新华网,2011.
[97]大秦铁路在煤炭运输中的重要作用.中国煤炭网.http: //www.zgmt.com.cn/.2011-10-18.
[98]需求推动价格回升,煤炭盈利再现快增.搜狐证券.http: //stock.sohu.com/20110429/n280454004.shtm.2011-4-29.
[99]阎颐.大物流工程项目类制造系统供应链协同及评价研究[D].天津：天津大学,2007.
[100]金乐琴.企业社会责任与可持续发展：理论与对策[J].绿色中国,2004(2)：50-52.
[101]п.c.格伦托夫.车站运营可靠性[M].陈秀凤,阎长安.译.第一版.北京：中国铁道出版社,1991.
[102]国外铁路.铁路运输与经济[J].2006(05)：91.
[103]徐中伟,黄银霞,呼爱蝉等.安全评估国际标准转化框架体系的研究[J].铁道技术监督,2008(1)：6-11.
[104]余静,卢明银.矿区铁路运输管理信息系统的可靠性设计[J].IM&P化工矿物与加工,2006(3)：26-28.
[105]才庆祥,余静.矿区铁路运输系统可靠性研究[J].煤炭学报,2004(10)：536-539.
[106]蔡金,高自友.铁路安全预警系统的研究和实现[J].中国安全科学学报,2003(3)：18-21.
[107]李阳,高自友.铁路安全预警系统的研究与设计[J].中国安全科学学报,2004(6)：36-40.
[108]范振平,林伯梁,李俊卫.铁路局安全预警系统研究[J].交通运输系统工程与信息,2006(12)：149-152.
[109]付国轩.多式联运可靠性研究[D].北京：北京交通大学,2008.
[110]陈红霞.以微机为基础的铁路信号设备可靠性设计与分析[D].成都：西南交通大学,2005.
[111]杨媛,吴俊勇,吴燕等.基于可信性理论的电气化铁路接触网可靠性的模糊评估[J].铁道学报,2008,12：115-119.
[112]陈绍宽,毛保华,何天健等.基于事故树分析的铁路牵引供电系统可靠性评价[J].铁道学报,2006,28(6)：123-129. [113]王灵芝,徐宇工,张家.铁路设备关键零部件的可靠性分析模型及其应用
研究[J].铁道学报,2008,30(4)：93-97.[114]李夏苗,胡思继,朱晓立.直达货物运输按时送达可靠性的评估方法[J].中
国铁道科学,2003,24(1)：121-124.[115]林柏梁,朱松年.路网上车流径路与列车编组计划的整体优化[J].铁道学
报,1996,18：17-18.[116]曹学明,林后梁,严贺祥.装车地直达货物列车开行优化模型[J].中国铁
道科学,2006,28(4)：6-11.[117]李宏.国外重载铁路综述[J].铁道工程学报,2000,4：32-34.[118]熊琴.装车地直达列车编组计划近似优化研究[D].北京：北京交通大学,
2006.[119]於明敏.大宗货物直达列车开行可靠性研究[D].长沙：中南大学,2010.[120] Algirdas. A, Laprie. J. C, Randel. B, etal. Basic concepts and taxonomy
of dependable and secure computing[J]. IEEE Transactions on Dependable and Secure
Computing,2004,1(1):11-33. [121] Colliins. J. A. Failure of Materials in Mechanical Design:Analysis, Prediction,
and Prevention[J]. New York:John Wiley & Sons,1993,34.[122]金星,洪延姬.系统可靠性与可用性分析方法[M].北京：国防工业出版
社,2007,22-27.[123]林闯,王元卓,杨扬等.基于随机Petri网的网络可信赖性分析方法研究.电
子学报[J],2006(2)：322-332.[124]梅启智,廖炯生,孙惠中.系统可靠性工程基础[M].北京：科学出版社,
1992：53-59.[125] Trivedi. K. S. Probability and Statistics with Reliability, Queuing and Computer
Science Applications [M]. Second. New York:John Wiley and Sons,2001. [126] Bondavalli. A., Chiaradonna. S, Giandomenico. F. D& Mura. I. Dependability
Modeling and Evaluation of Multiple-Phased Systems Using DEEM[J], IEEE
Transactions on Reliability,2004,53(4):509-522. [127] LIN. Chuang, WEIYa. Ya. Stochastic process algebras and stochastic
Petrinets[J]. Journal of software,2002,13(2):203-213. [128] Lin.C, Marinescu. D C. Stochastic high-level Petri nets and applications[J].
IEEE Transactions on Computers,1988,37(7):815-825. [129] LI. Zhen-lie, YANG. Xia-fang. Fault tree analysis on train rush without
permission from signals [J]. Beijing:Railway Transport and Economy,2002,24(4): 27-28.
[130]Hudoklin. A,&Rozman. V. Safety analysis of the railway traffic system. New York:Reliability E ngieering & System Safety,1992,37(1):7-13.
[131]Goodman. G. V. R. An assessment of coal mine escapeway reliability using fault tree analysis. New York:Mining Science and Technology,1988,7(2):205-215.
[132]JIA. Zhi-wei, JING. Guo-xun,&ZHANG. Qiang, etal. Fault tree analysis of mining fire occurrence based on triangle fuzzy numerals. Beijing:Journal of Safety and Environment,2004,4(6):62-65.
[133]Oh. Y, Yoo. J, Cha. S, etal. Software safety analysis of function block diagrams using fault trees. New York:Reliability Engineering and System Safety,2005, 88(3):215-228.
[134]Towhidnejad. M, Wallace. D. R,& Gallo. A.M. Fault tree analysis for software design. New York:IEEE Software engineering workshop.2002:24-29.
[135]Balbo. G.. Introduction to Stochastic Petri Nets[M]. Berlin:Springer-Verlag, 2001:84-155.
[136]林闯.随机Petri网和系统性能评价[M].北京：清华大学出版社,2000-01.
[137]罗航.故障树分析的若干关键问题研究[D].西安：电子科技大学,2006.
[138]杨纶标,高英仪.模糊数学原理及应用[M].广州：华南理工大学出版社.
[139]原菊梅.复杂系统可靠Petri网建模及其智能分析方法[M].北京：国防工业出版社,2011.
[140]秦英孝等.可靠性、维修性、保障性概论[M].北京：国防工业出版社,2002,24-25.
[141]门可佩.基于经济系统的中国协调发展指数实证研究[J].技术经济,2010,29(9)：37-41.
[142]武旭,胡思继,崔艳萍,马叶江.铁路运输与社会经济协调发展评价问题的研究[J].铁道学报,2005,27(6)：20-25.
[143]铁道部运输局.关于全路建设战略装车点的指导性意见[J].铁道货运,北京,2006：44-46.
[144]胡松超.推进铁路货运集约化经营问题的探讨[J].铁道货运,北京,2007,5：12-14.
[145]胡松超,吴方针.推进点线能力协调适应铁路运输发展[J].铁道运输经济,北京,2006,1：6-7.
[146]李维平.培育战略装车点提高铁路运输能力[J].铁道运输与经济,2006,28(11)：10-11.
[147]武汛.坚持系统集成与自主创新相结合全面提高大秦铁路重载运输能力[J].铁道运输与经济,2007,(10)：50-52.
[148]武汛.推进战略装车点建设的探索与实践[J].中国铁路,2008：3-7.
[149]纪丽君,林柏梁.战略装车点选址模型研究[J].铁道学报,2008(5)：8-11.
[150]纪丽君,林柏梁.战略装车点多点选址模型及算法[J].北京交通大学学报,2009,33(6)：32-35.
[151]杨新伟.不同劳动类型职工个体特征与工作能力关系研究[J].四川大学学报：医学版,2003,34(4)：724-126.
[152]张学珍.铁路运输企业薪酬管理的问题与调整建议[D].北京：北京交通大学,2005.
[153]刘泽云.教育与工资不平等：中国城镇地区的经验研究[J].统计研究,2009,26(4)：53-59.
[154]王毅,高源.压缩车站停时加速车辆周转[J].铁道运输与经济,2004,27(2)：46-47.
[155]于伯良.压缩货车周转时间的研究[J].经营管理者,2010(22)：237.
[156]张靠社.刘广武.压缩专用线货车停留时间的措施[J].铁道运输与经济,2010,33(3)：39-63.
[157]吴彩兰.重载铁路扩能研究[J].铁道标准设计,2005(6)：14-18.
[158]李磊,崔炳谋.基于混合算法的编组站到发线模型算法研究[J].交通运输工程与信息学报,2008,6(1)：86-90.
[159]雷中林,何世伟.铁路路网系统运输能力灵活性研究[J].铁道学报,2009,31(1)：26-30.
[160]王韵茹,王慈光.铁路车站中时指标的组成分析法探讨[J].铁道运输与经济,2010,32(9)：73-76.
[161]彭其渊,王慈光.铁路行车组织[M].北京：中国铁道出版社,2007：51.
[162]蒙全芳,潘俊杰.铁路运输货车周转时间计算方法的探讨[J].甘肃科技,2005,21(7)：111-112.
[163]张金丰.宽堆场标准垛堆料工艺的研究.港口装卸,2010(5)：40-42.
[164]赵金业.秦皇岛港可持续发展中的环境保护对策研究[D].保定：华北电力大学,2006.
[165]丁晓平.秦皇岛港煤四期码头堆场工艺设备的改进[J].港工技术,2004(4)：13-28.
[166]季永利,王庆利.堆取料机仓位和堆端位置信号的动态监测[J].水泥技术,2001(3)：40-41.
[167]应光伟.斗轮堆取料机的发展与展望[J].港口装卸,2010(4)：1-4.
[168]陈洋.船舶在港停泊时间的影响因素分析[J].珠江水运,2009(11)：70-71.
[169]汪传旭.交通运输与经济发展协调程度的定量评价[J].上海海运学院学报,1999,20(3)：96-102.
[170]张生瑞.公路交通可持续发展系统分析与评价[D].西安：长安大学,2002.
[171]王孝坤.综合运输复合系统协调发展研究[D].西安：长安大学,2003.
[172]张生瑞,邵春福.交通运输系统协调发展理论与模型研究[J].数学的实践与认识,2007,37(6)：1-6.
[173]付慧敏.运输通道公铁系统协调发展研究[D].西安：长安大学,2006.
[174]吴群琪.综合运输体系价值分析理论研究[D].西安：长安大学,2000.
[175]郭均鹏.区间评估理论方法与应用研究[D].天津：天津大学,2003.
[176]太原铁路局运输处.太原铁路局汇报材料,2012,1.
[177]程碧荣.重载铁路集疏运系统协调研究[D].长沙：中南大学,2011.
[178]王军.提高北同蒲线及相关线路运输能力的探讨[J].铁道运输与经济,2010(7)：37-39.
[179]牛会想.大秦铁路通过能力计算的特殊性分析[J].铁道工程学报,2009(8)：53-56.
[180]刘庆伟.宝钢普铁系统能力查定、评估及加强方案研究[D].成都：西南交通大学,2004.
[181]大秦车务段曹妃甸西站电煤卸车创新高.中国铁道网,http: //www.railcn.net/taiyuan/176403.html.2012-2-22.
[182]国投京唐港卸车量创新高.http://forum.10jqka.com.cn/c/20110530/522687 988.shtml.2011-5-30.
[183]曾琢.枣阳市土地利用协调发展评价研究[D].武汉：华中农业大学,2009.
[184]刘文,杨月芳.长大干线设计中点线能力协调刍议[J].兰州铁道学院学报：自然科学版,2002(4)：111-114.