This paper aims to develop appropriate solutions for each of the causes for the change orders, which help to manage the cost risk in road projects in Iraq. The literature was reviewed in detail, and the objectives were implemented by using a questionnaire that was distributed to specialists in the public sector to survey all possible causes for exceeding the cost of road projects. As a result, 35 causes were identified for a large number of change orders in road projects and their classification into four axes: design, implementation, financial, and other causes. The results of the questionnaire were analyzed using the relative importance index (RII). As a result, the main causes of the change orders were the variations in design and the quantities of work. The main effect was found to be an increase in the cost of the project. Finally, solutions were collected for each of the factors causing the change order through personal interviews with professionals and consultants.

Road construction projects in Iraq require a developmental study of the planning process toward building computerized management systems. In this thesis, a management system has been built, based on artificial neural networks and genetic algorithms. The proposed software estimates the optimal number of equipment, machineries, and relevance instruments required according to progress table of the work during the proposed implementation period of the project. Artificial neural network systems have been adopted to build models to predict the productivity of the equipment used in road construction projects, based on the factors that affecting the productivity of these mechanisms. By implementing the system and simulating at road project, several conclusions have been conducted. One of the most important conclusions is that the optimal distribution of the numbers and types of machineries used in road construction has a significant impact on the time of implementation of project.