A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Automated multi-objective construction logistics optimization system
https://orcid.org/0000-0002-6601-9498
Abstract Construction 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.
Highlights An automated system was developed to integrate site and supply logistics. Logistics and layout decisions are optimized using genetic algorithms. Spatial data are automatically retrieved from the project's BIM file. A comprehensive database module was developed to host project logistics data.
Automated multi-objective construction logistics optimization system
https://orcid.org/0000-0002-6601-9498
Abstract Construction 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.
Highlights An automated system was developed to integrate site and supply logistics. Logistics and layout decisions are optimized using genetic algorithms. Spatial data are automatically retrieved from the project's BIM file. A comprehensive database module was developed to host project logistics data.
Automated multi-objective construction logistics optimization system
https://orcid.org/0000-0002-6601-9498
Abstract Construction 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.
Highlights An automated system was developed to integrate site and supply logistics. Logistics and layout decisions are optimized using genetic algorithms. Spatial data are automatically retrieved from the project's BIM file. A comprehensive database module was developed to host project logistics data.
Automated multi-objective construction logistics optimization system
Said, Hisham (author) / El-Rayes, Khaled (author)
Automation in Construction ; 43 ; 110-122
2014-03-12
13 pages
Article (Journal)
Electronic Resource
English
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