Abstract
Generally, a contingency cost is provided in a project to cover the change orders (CO) that may be generated in a project during the construction phase due to various reasons, such as unforeseen conditions, design errors, and scope changes. If the contingency cost could be accurately estimated during the contract's procurement phase, the CO cost could be properly managed during the construction phase. Traditionally, contingency costs are allocated around 10% to 15% of the project cost without considering any of the historical CO costs. In this study, a tool was developed to estimate the contingency cost of a road maintenance contract by using a mathematical model. The tool forecasts the contingency costs for each of the road maintenance activities included in the contract by using an artificial neural network model based on the historical CO data. The tool was validated using the CO cost data available from road maintenance contracts.
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