Extended Genetic Algorithm for Optimized BIM-Based Construction Scheduling (original) (raw)
2018, Wiley StatsRef: Statistics Reference Online
Construction project scheduling is one of the most important tools for project managers in the architecture, engineering, and construction (AEC) industry. Construction schedules allow project managers to track and manage the time, cost, and quality (i.e., the project management triangle) of projects. Developing project schedules is almost always troublesome, as it is heavily dependent on project planners' knowledge of work packages, on-the-job experience, planning capability, and oversight. Having a thorough understanding of the project geometries and their internal interacting stability relations plays a significant role in generating practical construction sequencing. On the other hand, the new concept of embedding all the project information into a three-dimensional (3D) representation of a project (also known as building information model or BIM) has recently drawn the attention of the construction industry. It seems timely to use this source of project data for generating better construction schedules. In this article, the authors demonstrate how to develop and extend the usage of the genetic algorithm (GA), not only to generate construction schedules, but also to optimize the outcome for different objectives (i.e., cost, time, and job-site movements). The proposed methodology initially generates structurally stable construction schedules and then optimizes these schedules based on three distinct project management objectives. The basis for the GA calculations is the embedded data available in the BIM of the project, which should be provided as an input to the algorithm. By reading the geometric information in the 3D model and more specific information about the project and resources from the user, the algorithm results in various construction schedules. The output 4D animations and schedule quality scores can further help the user to find the most suitable construction schedules for the given project.