Optimizing construction time and cost using ant colony optimization approach

Time and cost are the most important factors to be considered in every construction project. In order to maximize the return, both the client and contractor would strive to optimize the project duration and cost concurrently. Over the years, many research studies have been conducted to model the time-cost relationships, and the modeling techniques range from the heuristic methods and mathematical approaches to genetic algorithms. Despite that, previous studies often assumed the time being constant leaving the analyses based purely on a single objective-cost. Acknowledging the significance of time-cost optimization, an evolutionary-based optimization algorithm known as ant colony optimization is applied to solve the multiobjective time-cost optimization problems. In this paper, the basic mechanism of the proposed model is unveiled. Having developed a program in the Visual Basic platform, tests are conducted to compare the performance of the proposed model against other analytical methods previously used for time-cost modeling. The results show that the ant colony system approach is able to generate better solutions without utilizing much computational resources which provides a useful means to support planners and managers in making better time-cost decisions efficiently.