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基于决策树机场电动及燃油特种车辆任务分配

费春国,尚德轩   

  1. (taptap下载安装安卓电子信息与自动化学院,天津300300)
  • 收稿日期:2017-01-10 修回日期:2017-03-08 出版日期:2017-08-25 发布日期:2017-11-08
  • 作者简介:费春国(1974—),男,浙江慈溪人,副教授,博士,研究方向为神经网络优化算法、机场车辆调度优化算法、电力系统负载优化和工业控制等.
  • 基金资助:

    国家自然科学基金项目(61403395)

Task assignment of electric and fuel special vehicles based on decision tree

FEI Chunguo, SHANG Dexuan   

  1. (College of Electronic Information and Automation, CAUC, Tianjin 300300, China)
  • Received:2017-01-10 Revised:2017-03-08 Online:2017-08-25 Published:2017-11-08

摘要:

 航班延误的主要原因之一是机场地面特种车辆调度失误。随着机场地面特种车辆野油改电冶的进行,机场将引入电动特种车辆和充电桩,在对电动特种车辆进行任务分配和调度过程中将面临一些新的问题。在电动特种车辆引入的初期,势必需要研究一种新的方案以解决燃油特种车辆和电动特种车辆共存条件下面临的任务分配问题。本研究通过ID3 决策树算法对两种特种车辆状态数据进行分析归纳,构建决策树和生成决策规则集合,得出决策模型,对两种特征车辆进行合理的任务分配。结果表明:该方法能够有效准确地解决特种车辆任务分配问题,与传统方法相比,能够有效降低人为因素引起的失误,以提高地面特种车辆的运行效率。

关键词: 调度, 决策树算法, ID3 算法, 特种车辆任务分配, 分支

Abstract:

One of the main reasons of flight delay is the failure of airport ground vehicle allocation. With the airport ground special vehicle change from oil-driven to electricity-driven, electric vehicles and charging pile will be introduced, and the electric vehicle assignment and scheduling process will face new problems. In early stage of the introduction of electric vehicles, it is necessary to study a new scheme to solve the problem of task allocation under the coexistence of special oil vehicles and special electricity vehicles. The ID3 decision tree algorithm of two kinds of special vehicle state data are analyzed and summarized, and decision tree is constructed to generate decision rules set as well as decision model of task allocation for two kinds of characteristics of the vehicle. Results show that the proposed method can effectively and accurately solve the task assignment problem of special vehicles. Compared with the traditional methods, this method can effectively reduce the errors caused by human factors and improve the operation efficiency of special vehicles.

Key words: scheduling, decision tree algorithm, ID3 algorithm, task assignment of special vehicles, branch

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