Optimization the Number and Place of Pavement ConditionSurveyed Inspection Units Using GA
عنوان مقاله: Optimization the Number and Place of Pavement ConditionSurveyed Inspection Units Using GA
شناسه ملی مقاله: CESC15_328
منتشر شده در پانزدهمین کنفرانس دانشجویان عمران سراسر کشور در سال 1393
شناسه ملی مقاله: CESC15_328
منتشر شده در پانزدهمین کنفرانس دانشجویان عمران سراسر کشور در سال 1393
مشخصات نویسندگان مقاله:
Ashkan Allahyari Nik - M.Sc. Student, Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran,
Fereidoon Moghadas Nejad۲ - Associate Professor, Department of Civil and Environmental Engineering, Amirkabir University, Tehran, Iran
Alireza Khavandi Khiavi۳ - Assistant Professor, Department of Civil Engineering, Zanjan University, Tehran, Iran
خلاصه مقاله:
Ashkan Allahyari Nik - M.Sc. Student, Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran,
Fereidoon Moghadas Nejad۲ - Associate Professor, Department of Civil and Environmental Engineering, Amirkabir University, Tehran, Iran
Alireza Khavandi Khiavi۳ - Assistant Professor, Department of Civil Engineering, Zanjan University, Tehran, Iran
Determine the pavement condition is important part of pavement management for selecting the maintenance and rehabilitation (M&R) activities. It is required to a visual inspection and the first step is dividing pavement sections of a network into smaller units as inspection units. Surveying all of these is costly and time consuming for transportation agencies. So the strategies for selecting specific number of inspection units as surveyed inspection units are appliedfor acceptably accurate pavement condition. In this paper develops genetic algorithm (GA) for determining pavement condition with optimal number and place of surveyed inspection units. The results of this paper show GA is applicative for solving the present problem and it helps to managers and human inspectors for optimal decision in inspection process and M&R activities. The numerical results describe that the 60% of surveyed inspection units achieved to optimal network for case study pavement network
کلمات کلیدی: Pavement Management, Pavement Condition, Genetic Algorithm, Surveyed Inspection Units,Maintenance and Rehabilitation activities
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/321857/