Abstract

Project planning can be treated as an optimization problem focused on organizing a set of tasks while respecting a set of precedent constraints and the limited use of renewable and non-renewable resources. The resulting schedule must have the properties of being executed with the least possible time and cost and with a balanced quality of the solution. In this research, a set of new distribution estimation algorithms is presented to solve this problem. Furthermore, the behavior of different evolutionary algorithms in the construction of schedules is compared. The experimental results show the viability of evolutionary algorithms for the agile construction of chronograms and their potential use in BIM environments. In the experimentation, a set of 150 instances collected in 15 databases from the PSPLib library were used. The sensitivity of the behavior of the algorithms is evaluated in the following scenarios: variation in the number of execution modes, in the number of tasks, in the number of renewable resources, and in the number of non-renewable resources, demonstrating the feasibility of the solutions.