Outline

Ingegneria Sismica

Ingegneria Sismica

Research on high-rise building construction cost optimization based on BIM and genetic Algorithm

Author(s): Ruiyang Liu1, Yang Su2, Ke Li3
1Department of Architectural Engineering of Taishan Polytechnic, Taian, 271000, Shandong, China
2Linyi Procuratorial Affairs Center, Linyi, 270634, Shandong, China
3Independent Author, Jinan, 250000, Shandong, China
Liu, Ruiyang., Su, Yang., and Li, Ke. “Research on high-rise building construction cost optimization based on BIM and genetic Algorithm.” Ingegneria Sismica Volume 43 Issue 1: 1-21, doi:10.65102/is2026228.

Abstract

Aiming at the problems of complex cost composition, strong coupling of resource constraints and response lag of static control methods in the construction process of high-rise buildings, this paper proposes a construction cost optimization method based on BIM and genetic algorithm. BIM is used as the unified information carrier to construct the component-task-resource-expense integrated cost model, and the construction state is mapped to the computable optimization node through the structural design of task-cost unit. On this basis, genetic algorithm is introduced to realize the rolling optimization and scheme reconstruction for dynamic construction conditions. The experiment was carried out on the dataset of 32-floor residential project. The results show that the cost compression rate of the proposed method reaches 12.8%, which is 7.9 percentage points and 5.4 percentage points higher than that of the traditional method and the BIM static optimization method respectively. The time deviation rate is reduced to 3.6%, the resource utilization rate is increased to 86.7%, the average re-optimization response time is only 2.1 s, and the instability rate of the scheme is controlled at 2.9%. Research shows that this method can maintain good cost control ability and execution stability under complex construction disturbances, and provide a landing calculation path for digital cost control of high-rise buildings.

Keywords
BIM; Genetic algorithm; High-rise building construction; Cost optimization

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