Prediction of Optimal Maintenance Alternative for Iraqi Pavement Management Based on Multi-Objective Optimization Technique and Constraint Genetic Algorithm

Abstract

Pavement management systems (PMS) are widely used to assist the transportation agencies to support the decision makers to select the best maintenance alternatives. To maintain a pavement network under a performance-based efficiently and cost-effectively in a long-term horizon, the local related agencies such as SCRB, mayoralty of Baghdad and Ministry of Municipalities need to provide balance multiple objectives (e.g., cost minimum, performance maximum) which are often different from the requirements of the traditional asset preservation practices. Accordingly, the main objective of this research is to develop a multi-objective optimization model to support the multi-year decision making process of the Iraqi pavement maintenance management system. Two optimization objectives are considered; maintenance cost minimization and pavement condition maximization. This study selects the flexible pavement section (R4/B-Expressway No.1) as the study area. Different field measurements are carried out to estimate the pavement performance indicators (PPI) which included; Pavement Condition Index (PCI), International Friction Index (IFI), and International Roughness Index (IRI) to formulate multi-objective optimization models to select optimal maintenance alternative for the selected case study. Keywords: pavement management system, pavement maintenance, multi-objective optimization, genetic algorithm