Fereidoon Moghadas Nejad - Associate Professor, Dept. of Civil and Environmental Engineering, Amirkabir University, Tehran, Iran
Ashkan Allahyari Nik - M.Sc. Student, Highway and Transportation Engineering, Dept. of Technical and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
H. Zakeri - PhD Candidate, Dept. of Civil and Environmental Engineering, Amirkabir University, Tehran, Iran

Pavement condition index (PCI) is an important index in pavement management that is required toinspection process for estimating it. First step in this process is dividing pavement sections into smallerunits as inspection units. Inspecting all of the units is needed to high cost and time, therefore samplingplan must be somehow inspecting specific number of the inspection units as surveyed inspection units canestimate with the lowest error in PCI. The main purpose of this paper is to use and develop GA forestimating PCI with optimal arrangement of surveyed inspection units. A pavement network as a casestudy was applied for demonstrating the effect of proposed GA. Results of this research can helpmanagers and inspectors for better decision making in inspection process.

Pavement Management, Pavement Condition Index, Genetic Algorithm, Surveyed Inspection Units, Optimal arrangement