Said, H., T. Nicoletti, and P. Perez-Hernandez, "Utilizing Telematics Data to Support Effective Equipment Fleet-Management Decisions: Utilization Rate and Hazard Functions", Journal of Computing in Civil EngineeringJournal of Computing in Civil Engineering: American Society of Civil Engineers, pp. 04014122, 2014. Abstractsaid-etal-2014_telematicsfleetmngmnt.pdfWebsite

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Lucko, G., H. M. M. Said, and A. Bouferguene, Construction Spatial Modeling and Scheduling with Three-dimensional Singularity Functions, , vol. 43, pp. 132 - 143, 2014/7//. Abstract2014_constrspatialmodelsched-3d_singularity.pdfWebsite

AbstractPrevious approaches for construction project scheduling have been limited to one dimension of time for bar charts and two dimensions for linear and repetitive scheduling approaches, which added a measure of work quantity. The question therefore arises if and how it is possible to derive a three-dimensional and ultimately multi-dimensional model. Reviewing mathematical theory finds that traditional functions lack the capability to express intervals for activities. Singularity functions are therefore chosen to newly derive stationary and directional activities in a Cartesian coordinate system, wherein the two dimensions of the floor plan area plus one dimension of time are explicitly modeled in an integrated manner. They are implemented into a conflict-avoiding heuristic scheduling algorithm that minimizes total project duration, which is computerized and validated with example calculations.

Said, H., and K. El-Rayes, Automated Multi-objective Construction Logistics Optimization System, , vol. 43, pp. 110 - 122, 2014/7//. Abstract2014_amclos.pdfWebsite

AbstractConstruction logistics planning entails the coordination of supply and site activities by integrating their decisions and recognizing existing interdependencies to minimize the total material management cost. Despite the preliminary estimates of its benefits to the construction industry, few contractors adopted logistics management because of its demand for detailed data and decision of material supply and site operations. This paper presents the development of a new automated multi-objective construction logistics optimization system (AMCLOS) that would support the contractors in optimally planning material supply and storage. AMCLOS provides a holistic framework of automatically retrieving project spatial and temporal data from existing scheduling and BIM electronic files, seamlessly integrating relevant contractor and suppliers' data, and optimizing material supply and site decisions to minimize total logistics costs. The performance of AMCLOS was validated against a previous construction logistics planning model, which provided useful insights on material supply and storage logistics in congested and spacious sites. The developed system is envisioned to increase the implementation of logistics management practices and early integration and coordination of construction supply and site processes.