Open AccessSelecting the Affected Factors on Pavement Distress Problems Using Analytical Hierarchy Process [AHP]
Author(s) -
Abdalrhman Milad,
Noor Ezlin Ahmed Basri,
Mohammad K. Younes,
Hassan. M.Abdelsalam,
Riza Atiq O.K. Rahmat
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.29.14004
Subject(s) - analytic hierarchy process , ranking (information retrieval) , pairwise comparison , distress , hierarchy , cracking , fatigue cracking , set (abstract data type) , process (computing) , civil engineering , engineering , computer science , operations research , forensic engineering , materials science , artificial intelligence , psychology , composite material , economics , market economy , psychotherapist , programming language , operating system
This study describes the implementation of analytical hierarchy process [AHP] in pavement multi-criteria selection problem solving. The practice of expressing flexible pavement distress priority is widely accepted. However, an insistent demand exists for a technique that allows decision makers to determine their priorities, rational weights of the importance of pavement distress priority and the ranking of these factors. In this study, AHP is adopted in selecting the best level of distress in flexible pavements in Malaysia as an example of a tropical region. Knowledgeable and experienced experts in flexible pavement maintenance at jabatan kerja raya [JKR] and Kumpulan Ikram Sdn Bhd [IKRAM] were interviewed; as pairwise comparisons, their inputs were structured. Four criteria are set as follows: cracking, surface defects, surface deformations and patching and potholes. These criteria developed into a few other sub-criteria. Results show that cracking is the most significant factor [0.5500], followed by surface deformations [0.2300], patching and potholes [0.1600] and surface defects [0.0600]. Thus, cracking has the most significant distress among the four factors.