This paper presents a work-item-based scheduling system that employs MD CAD model, Object Sequencing Matrix (OSM), and Genetic Algorithms (GAs) to generate the time-cost integrated schedule for construction projects. Consisting of MD CAD objects, the MD CAD model ensures the consistency and efficiency of information processing and integration in project planning. In the development of MD CAD model-based scheduling system, the Object Sequencing Matrix (OSM) is adopted to formulate a construction sequence of building components based on the physical relationships between MD CAD objects. Genetic algorithms (GAs) are then applied to optimize the sequence of building components and the assignment of crews. As a result, a feasible time-cost integrated project schedule is developed. In computer implementation, the MD CAD model-based Project Scheduling System (MD-PSS) is presented to verify the feasibility of the proposed approach.
Researchers have been studying early planning process since the early 1990's and results from these researches suggest that projects with more early planning efforts are more likely to succeed. This study intends to employ neural networks to build credible models linking preproject planning and project success. Preproject planning status as measured by Project Definition Rating Index (PDRI) is set as the independent variable and schedule/cost performance is set as dependent variable. To enhance the performance of the neural networks model, bootstrap aggregation and boosting algorithms are incorporated in the model development process. The results from these two neural network ensemble models are examined. This research finds out that boosting neural network ensemble models produce better results than bootstrap aggregation neural network ensemble models. Results from both models show that project with better early planning can expect better chance of project success.
The maintenance of landscape construction projects exhibits several distinct features including long life cycles, high costs, and a variety of influencing factors. Landscape information modeling (LIM), developed based on the concept of building information modeling (BIM), has been applied in landscape design with several preliminary achievements. However, the current database structure associated with a landscape information model does not include any information required for the maintenance of a landscape project. Therefore, this study focused on the maintenance and management of landscape projects. Specifically, we first presented a detailed discussion on the information requirement for the maintenance and management of landscape projects. Based on these requirements, a building information model for describing the maintenance information is established. Finally, a BIM-based landscape maintenance and management system is developed and validated with a practical case study. The case study reveals high integrity, mobility, and effectiveness of the collected information for use in landscape maintenance. In addition, instantaneous visualization of the information is also demonstrated in the study, which provides great convenience for practical maintenance work.
Information processing is critical to the successful development and execution of a construction project plan. Currently, Building Information Modeling (BIM) has been widely used in representing the physical and functional characteristics of design and construction. However, in order to use BIM effectively in construction project planning, more construction knowledge should be transformed and integrated. This paper proposes an activity-based modeling approach to process project information in an organized manner and proposes a Multi-Dimensional (MD) CAD model. The MD CAD model is composed of the MD CAD objects. The model can assist project planners in assessing information concerning the interrelationships between schedule, cost, resources, and work areas. A computer implementation called MD-Construction Project Management Information System (MD-CPMIS) is presented to verify the feasibility of the proposed approach.
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