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Automated Resource Scheduling for Construction Projects Using Genetic Algorithm
Site advance methods for planning and scheduling are essential for effective project management. Typically, construction managers tend to produce schedules based on two constraints: (1) Minimize Project Duration and (2) Allocate Minimum Resources. Moreover, deficits in the cash flow result in reduced profits at the end of the project and delays if financing problems arise, which results in damages (usually additional costs). Traditional scheduling tools like the Critical Path Method (CPM) and Time Constrained Project Scheduling Problem (TCPSP) do not show high efficiency in achieving the required objectives, as scheduling gets complicated. Advanced planning and scheduling methods will be used to produce a feasible schedule that meets specific objectives. This paper proposes a multi-objective model, (1) minimum project duration, (2) resource availability, and (3) minimum cash flow deficit. The model is divided into two modules. The first module produces an optimized, automated schedule achieving the objective of minimum project duration. The second module applies an optimized resource constraint scheduling using user input data of the available resources to allocate the resources on each activity while maintaining the maximum number of resources on site. The model is optimized using an evolutionary algorithm, namely: Genetic Algorithm (GA).
Automated Resource Scheduling for Construction Projects Using Genetic Algorithm
Site advance methods for planning and scheduling are essential for effective project management. Typically, construction managers tend to produce schedules based on two constraints: (1) Minimize Project Duration and (2) Allocate Minimum Resources. Moreover, deficits in the cash flow result in reduced profits at the end of the project and delays if financing problems arise, which results in damages (usually additional costs). Traditional scheduling tools like the Critical Path Method (CPM) and Time Constrained Project Scheduling Problem (TCPSP) do not show high efficiency in achieving the required objectives, as scheduling gets complicated. Advanced planning and scheduling methods will be used to produce a feasible schedule that meets specific objectives. This paper proposes a multi-objective model, (1) minimum project duration, (2) resource availability, and (3) minimum cash flow deficit. The model is divided into two modules. The first module produces an optimized, automated schedule achieving the objective of minimum project duration. The second module applies an optimized resource constraint scheduling using user input data of the available resources to allocate the resources on each activity while maintaining the maximum number of resources on site. The model is optimized using an evolutionary algorithm, namely: Genetic Algorithm (GA).
Automated Resource Scheduling for Construction Projects Using Genetic Algorithm
Lecture Notes in Civil Engineering
Gupta, Rishi (editor) / Sun, Min (editor) / Brzev, Svetlana (editor) / Alam, M. Shahria (editor) / Ng, Kelvin Tsun Wai (editor) / Li, Jianbing (editor) / El Damatty, Ashraf (editor) / Lim, Clark (editor) / Moharram, Raghda M. (author) / Essawy, Yasmeen A. S. (author)
Canadian Society of Civil Engineering Annual Conference ; 2022 ; Whistler, BC, BC, Canada
Proceedings of the Canadian Society of Civil Engineering Annual Conference 2022 ; Chapter: 32 ; 513-522
2023-08-17
10 pages
Article/Chapter (Book)
Electronic Resource
English
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