Applying ant colony optimization algorithm to optimize construction time and costs for mass concrete projects

This article introduces a novel approach to optimize costs and time in the construction of mass concrete projects by implementing the Ant Colony Optimization (ACO) algorithm. To achieve this, it is crucial to identify key factors influencing the construction process of mass concrete projects, such as the type of concrete, material cooling temperature, poured concrete layer height, and the frequency between concrete pumping intervals. Furthermore, the selection of these factors should be done with care to ensure appropriate precautions are taken, as heat accumulation from cement hydration and the associated volume changes can lead to concrete cracking. Numerous prior studies have made advancements in addressing these challenges. One particularly effective algorithm that has been developed and applied is the ACO algorithm. The integration of the ant colony algorithm with the evaluation method for concrete cracking indices will be demonstrated through a practical example. The ensuing results will demonstrate the applicability of these approaches to real-world mass concrete projects.