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公路网改扩建决策优化双层规划模型
  • ISSN号:1671-1637
  • 期刊名称:《交通运输工程学报》
  • 时间:0
  • 分类:U491.13[交通运输工程—交通运输规划与管理;交通运输工程—道路与铁道工程]
  • 作者机构:[1]长安大学公路学院,陕西西安710064, [2]同济大学交通运输工程学院,上海201804
  • 相关基金:高等学校博士学科点专项科研基金项目(200807100001);教育部人文社会科学基金项目(11YJA630155)
中文摘要:

针对公路网改扩建问题,在决策优化过程中,考虑了技术、资金、环境保护以及运营效率等因素。以路网系统的最小交通量为上层模型目标函数,以最小走行时间为下层模型目标函数,以路段服务水平、土地占用状况、建设投资等为约束条件,构建了公路网改扩建决策优化双层规划模型。采用遗传算法求解模型,并通过济青北线的实例数据进行实证分析。计算结果表明:济青北线济南一淄博段、淄博青州段、青州一潍坊段的扩建优化指数分别为2.15、4.09、3.54,新建优化指数分别为1.87、3.09、2.73,相同路段的扩建优化指数均高于新建优化指数,与实际相符。可见,模型有效。

英文摘要:

Aiming at the reconstruction and expansion problems of highway network, the factors such as technique, fund, environmental protection and operation efficiency were considered during the decision optimization process. The minimum traffuc volume of highway network system was taken as the objective function of upper-level model, the minimum trip time was taken as the objective function of lower-level model, the service level of road section, land occupancy status and construction investment were taken as constraint conditions, and a bi-level programming model of decision optimization of reconstruction and expansion for highway network was set up. Genetic algorithm was used to solve the model, and empirical analysis was carried out by using the example data of Northern Jiqing Highway. Calculation result shows that the expansion optimization indexes of Jinan-Zibo section, Zibo-Qingzhou section and Qingzhou- Weifang section for Northern Jiqing Highway are 2.15, 4.09 and 3.54 respectively, while the newly-built optimization indexes of the road sections are 1.87, 3.09 and 2.73 respectively. The expansion optimization index is higher than the newly-built optimization index for each road section, which is close to actual experience, so the model is effective. 7 tabs, 2 figs, 12 refs

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期刊信息
  • 《交通运输工程学报》
  • 北大核心期刊(2011版)
  • 主管单位:中华人民共和国教育部
  • 主办单位:长安大学
  • 主编:陈荫三
  • 地址:西安市南二环路中段
  • 邮编:710064
  • 邮箱:jygc@chd.edu.cn
  • 电话:029-82334388
  • 国际标准刊号:ISSN:1671-1637
  • 国内统一刊号:ISSN:61-1369/U
  • 邮发代号:52-195
  • 获奖情况:
  • 国内外数据库收录:
  • 俄罗斯文摘杂志,波兰哥白尼索引,荷兰文摘与引文数据库,美国工程索引,美国剑桥科学文摘,英国科学文摘数据库,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版)
  • 被引量:13453