Construction Scheduling Using Genetic Algorithm Based on Building Information Model (original) (raw)

2014, Expert Systems With Applications

The construction project schedule is one of the most important tools for project managers in the Architecture, Engineering, and Construction (AEC) industry that makes them able to track and manage the time, cost, and quality (a.k.a. Project Management Triangle) of projects. Developing project schedules is almost always troublesome, since 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 3-dimentional representation of a project (a.k.a. Building Information Model or BIM) has recently drawn attention to the construction industry. In this paper, the authors demonstrate a novel approach of retrieving enough information from the BIM of a project and then develop construction sequencing for the installation of the project elements. For this reason a computer application is developed that can automatically derive a structurally (statically) stable construction sequence, using the concept of the Genetic Algorithm (GA). The term “structurally stable sequencing” in this article refers to the sequencing order of erection in which the structure remains statically stable locally and globally during the entire installation process. To validate the proposed methodology, the authors designed 21 different experiments and used the proposed method for generating stable construction schedules, which all were successfully accomplished. Therefore, this methodology proposes a novel approach of construction project application of the GA, as an Expert System tool.

Extended Genetic Algorithm for Optimized BIM-Based Construction Scheduling

Wiley StatsRef: Statistics Reference Online, 2018

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.

Genetic Algorithm: An Innovative Technique for Optimizing a Construction Project

2020

Time and cost are two basic objectives of any construction project. Optimization of these objectives is the main concern over the last three decades by the construction sectors. Many innovative techniques have been used by the construction companies to optimize the cost and time of a project. Genetic Algorithm (GA) method is one of the most advanced and widely used non-traditional search algorithms based on the mechanics of natural selection and natural genetics. The principle of natural selection is based on the “survival of the fittest” concept coined by Charles Darwin. It is neither an intelligent nor a smart algorithm but it searches for optimal solution in the solution space. The objective is to review GA as an optimizing technique used to generate high-quality solution for optimization process. Reproduction in GA is done by three sophisticated operators—selection, crossover and mutation through which optimal solution is found out only if the condition is true. Hence, GA method...

Smart optimization for mega construction projects using artificial intelligence

During practicing the planning process, scheduling and controlling mega construction projects, there are varieties of procedures and methods that should be taken into consideration during project life cycle. Accordingly, it is important to consider the different modes that may be selected for an activity in the scheduling, for controlling mega construction projects. Critical Path Method ''CPM'' is useful for scheduling, controlling and improving mega construction projects; hence this paper presents the development of a model which incorporates the basic concepts of Critical Path Method ''CPM'' with a multi-objective Genetic Algorithm ''GA'' simultaneously. The main objective of this model is to suggest a practical support for compound horizontally and vertically mega construction planners who need to optimize resource utilization in order to minimize project duration and its cost with maximizing its quality simultaneously. Proposed software is named Smart Critical Path Method System, ''SCPMS'' which uses features of Critical Path Method ''CPM'' and multi-objective Genetic Algorithms ''GAs''. The main inputs and outputs of the proposed software are demonstrated and outlined; also the main subroutines and the inference wizards are detailed. The application of this research is focused on planning and scheduling mega construction projects that hold a good promise to: (1) Increase resource use efficiency; (2) Reduce construction total time; (3) Minimize construction total cost; and (4) Measure and improve construction total quality. In addition, the verification and validation of the proposed software are tested using a real case study. ª 2014 Production and hosting by Elsevier B.V. on behalf

Automated Master Project Schedule for Construction Incorporating Building Information Model and IFC

2014

At the end of a predesign phase of a building design, it is essential for the consulting firm to be able to generate from the BIM design, take-off quantities and construction activities durations efficiently at a short timeframe to derive the cost budget estimates and schedule for project tendering purpose. However, these efforts require prior construction site experience and knowledge together with their association to the BIM and IFC construction component data to automate a Master Project Schedule. The research and development of the automated master project schedule is the focus of the project which will read IFC data from a BIM application and display the model while the data are distributed to a database repository. The automated project schedule can then be generated with the activities and timeline of each building component presented by floor levels and component types. Finally, the challenges in changes in the construction methods such as precast and/or cast in-situ, and t...

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