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A platform for research: civil engineering, architecture and urbanism
Optimization Tower Crane Location Based on Genetic Algorithm: Systematic Literature Review
During the construction phase, transporting materials is a crucial activity in construction projects. The placement of tower cranes is critical because it impacts project productivity, defines service areas for lifting needs, improves workflows, ensures safety, manages conflicts with equipment and structures, and may reduce operating time and costs. Creating a precise positioning technique is crucial, as relying on expert guesswork and trial-and-error techniques alone may not provide the appropriate level of accuracy. The Genetic Algorithm, combining natural selection and genetics, effectively manages various constraints and objectives. It excels at quickly exploring solutions and implementing them. Our systematic review, following the PRISMA methodology, investigated Genetic Algorithm application for positioning tower cranes in high-rise construction projects. The main focus of our study encompassed the factors involved in decision-making, operational limitations, as well as objective functions. The decision factors under consideration included tower crane model, number of cycles, supply and demand point coordinates, and possible crane position. Moreover, the limitations identified consisted of quantity, capacity, operational height, jib radius, supply and demand area capacity, and potential overlapping of tower cranes. Tower crane time, cost, hook loading and unloading timings, distances between supply and demand points, and sequencing are all components of the goal function. The study emphasizes the importance of optimizing tower crane placement through the use of the Genetic Algorithm. This involves considering a range of decision variables, constraints, and objective functions to increase construction project efficiency while also reducing operational costs.
Optimization Tower Crane Location Based on Genetic Algorithm: Systematic Literature Review
During the construction phase, transporting materials is a crucial activity in construction projects. The placement of tower cranes is critical because it impacts project productivity, defines service areas for lifting needs, improves workflows, ensures safety, manages conflicts with equipment and structures, and may reduce operating time and costs. Creating a precise positioning technique is crucial, as relying on expert guesswork and trial-and-error techniques alone may not provide the appropriate level of accuracy. The Genetic Algorithm, combining natural selection and genetics, effectively manages various constraints and objectives. It excels at quickly exploring solutions and implementing them. Our systematic review, following the PRISMA methodology, investigated Genetic Algorithm application for positioning tower cranes in high-rise construction projects. The main focus of our study encompassed the factors involved in decision-making, operational limitations, as well as objective functions. The decision factors under consideration included tower crane model, number of cycles, supply and demand point coordinates, and possible crane position. Moreover, the limitations identified consisted of quantity, capacity, operational height, jib radius, supply and demand area capacity, and potential overlapping of tower cranes. Tower crane time, cost, hook loading and unloading timings, distances between supply and demand points, and sequencing are all components of the goal function. The study emphasizes the importance of optimizing tower crane placement through the use of the Genetic Algorithm. This involves considering a range of decision variables, constraints, and objective functions to increase construction project efficiency while also reducing operational costs.
Optimization Tower Crane Location Based on Genetic Algorithm: Systematic Literature Review
Lecture Notes in Civil Engineering
Nia, Elham Maghsoudi (editor) / Awang, Mokhtar (editor) / Santosa, Febrian Aditama (author) / Adi, Tri Joko Wahyu (author) / Prihartanto, Eko (author)
International Conference on Architecture and Civil Engineering Conference : ; 2023 ; Putrajaya, Malaysia
2024-07-06
19 pages
Article/Chapter (Book)
Electronic Resource
English
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