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مقالات فارسیISIکنفرانسهاژورنالها

A Novel GA based Approach for Optimizing the Number and Place of Surveyed Pavement Inspection Units

محل انتشار: ششمین همایش ملی قیر و آسفالت ایران
سال انتشار: 1393
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 530

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لینک ثابت به این مقاله:
https://civilica.com/doc/590417

شناسه ملی سند علمی:

CAAM06_047

تاریخ نمایه سازی: 19 خرداد 1396

چکیده مقاله:

Evaluation of the pavement condition index (PCI) is a basic part of pavement management that is required to visual inspection process by human inspectors for evaluating it. This process is done by dividing the pavement sections to smaller units as inspection units in the first. Surveying all of these units achieve high cost and time.Therefore inspection must be conduct for a comprehensive plan that by surveying the specific number of inspection units as surveyed inspection units achieved to accurate PCI. In this research, a novel approach proposes based on genetic algorithm (GA) for evaluating the PCI with optimal number and place of surveyed inspection units as optimal arrangement. A pavement network as a case study was applied for demonstrating the effect of proposed approach. The results of this paper show the proposed approach is efficient for solving the present problem and it can achieve to optimal decision by managers and human inspectors for M&R activities

کلیدواژه ها:

Pavement Management ، Pavement Condition Index ، Genetic Algorithm ، Surveyed Inspection Units ، Optimal decision

نویسندگان

Ashkan Allahyari Nik

M.Sc. Student, Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran, ,

Fereidoon Moghadas Nejad

Associate Professor, Department of Civil and Environmental Engineering, University of Amirkabir, Tehran, Iran,

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  • roads Non-nationlه [7] Department of Environment, Heritage and Local Government. ...
  • pavement management report: phase Statewideه [8] Michigan Department of Transportation, ...
  • Moghadas Nejad, F., and Zakeri, H. (2013). The Hybrid Method ...
  • Shahin, M. Y. (2005), "Pavement management for airports, roads and ...
  • Mishalani, R.G., and Gong, L. (2009), "Optimal infrastructure condition sampling ...
  • Yu, B., Lu, Q., and Xu. (2013), _ improved pavement ...
  • Su, Y.S., Kang, S.C., Chang, J.R., Hsieh, S.H. (2013), "Dual-Light ...
  • Buddhavarapu, P., Banerjee, A., and Prozzi, J.A. (2013), "Influence of ...
  • De la Garza, J.M., Piero, J. C., and Ozbek , ...
  • Texas Transportation Institute. (2010), _ of micro unmanned aerial vehicles ...
  • Oregon Department of Aviation, (2011), _ evaluation / maintenance management ...
  • ASTM D6433-11. (2011), "Standard practice for roads and parking lots ...
  • Negnevitsky, M. (2005), Artificial Intelligence: A guide to intelligent systems, ...
  • Lu, Ch., and Yu, V. F. (2012), :Data envelopment analysis ...
  • Sivanandam, S.N., and Deepa, S.N. (2008), Introduction to Genetic Algorithms, ...
    • نمایش کامل مراجع