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Optimized acceleration of repetitive construction projects
Abstract Contractors and/or owners frequently need to accelerate the delivery of construction projects. Contractors may have to accelerate in order to benefit from contractual bonus, avoid penalties, recover from delays and/or avoid undesirable weather and site conditions. Owners, on the other hand, may order acceleration to meat business and operational opportunities. This paper presents an algorithm for schedule updating, dynamic rescheduling and optimized acceleration of repetitive construction projects. Schedule updating captures the exact progress on site. Dynamic rescheduling aims at capitalizing on the repetitive nature of the project to fine-tune the remaining portion of the project. Optimized acceleration presents an optimized time–cost trade-off that is tailored for repetitive projects. Through a set of iterative steps, the optimized acceleration procedure divides each activity into segments and identifies the segments that would shorten project duration if accelerated. For those identified segments, the ones with the least cost slope are selected and queued for acceleration. Through the proposed segmentation of activities this algorithm provides optimum allocation of additional acceleration resources, thus is rendered capable of identifying least cost acceleration plans. The algorithm allows users to select among different acceleration strategies such as working overtime, working double shifts, working weekends, and employing more productive crews. The presented algorithm maintains work continuity and accounts for typical and non-typical activities. The algorithm is implemented in a spreadsheet application, which automates calculations, yet allows users to fine tune the algorithm to fit the project at hand. The developed algorithm is applied to a case study drawn from literature in order to illustrate its basic features and demonstrate its accuracy.
Optimized acceleration of repetitive construction projects
Abstract Contractors and/or owners frequently need to accelerate the delivery of construction projects. Contractors may have to accelerate in order to benefit from contractual bonus, avoid penalties, recover from delays and/or avoid undesirable weather and site conditions. Owners, on the other hand, may order acceleration to meat business and operational opportunities. This paper presents an algorithm for schedule updating, dynamic rescheduling and optimized acceleration of repetitive construction projects. Schedule updating captures the exact progress on site. Dynamic rescheduling aims at capitalizing on the repetitive nature of the project to fine-tune the remaining portion of the project. Optimized acceleration presents an optimized time–cost trade-off that is tailored for repetitive projects. Through a set of iterative steps, the optimized acceleration procedure divides each activity into segments and identifies the segments that would shorten project duration if accelerated. For those identified segments, the ones with the least cost slope are selected and queued for acceleration. Through the proposed segmentation of activities this algorithm provides optimum allocation of additional acceleration resources, thus is rendered capable of identifying least cost acceleration plans. The algorithm allows users to select among different acceleration strategies such as working overtime, working double shifts, working weekends, and employing more productive crews. The presented algorithm maintains work continuity and accounts for typical and non-typical activities. The algorithm is implemented in a spreadsheet application, which automates calculations, yet allows users to fine tune the algorithm to fit the project at hand. The developed algorithm is applied to a case study drawn from literature in order to illustrate its basic features and demonstrate its accuracy.
Optimized acceleration of repetitive construction projects
Bakry, Ibrahim (author) / Moselhi, Osama (author) / Zayed, Tarek (author)
Automation in Construction ; 39 ; 145-151
2013-07-05
7 pages
Article (Journal)
Electronic Resource
English
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