TY - GEN
T1 - Optimization Tower Crane Location Based on Genetic Algorithm
T2 - 7th International Conference on Architecture and Civil Engineering, ICACE 2023
AU - Santosa, Febrian Aditama
AU - Adi, Tri Joko Wahyu
AU - Prihartanto, Eko
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Genetic Algorithm
KW - Location
KW - Optimization
KW - Tower crane
UR - http://www.scopus.com/inward/record.url?scp=85200365283&partnerID=8YFLogxK
U2 - 10.1007/978-981-97-0751-5_44
DO - 10.1007/978-981-97-0751-5_44
M3 - Conference contribution
AN - SCOPUS:85200365283
SN - 9789819707508
T3 - Lecture Notes in Civil Engineering
SP - 473
EP - 491
BT - Advances in Civil Engineering Materials - Selected Articles from the 7th International Conference on Architecture and Civil Engineering ICACE 2023
A2 - Nia, Elham Maghsoudi
A2 - Awang, Mokhtar
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 15 November 2023 through 15 November 2023
ER -