Affiliation:
1. Department of Architectural Engineering, Kyung Hee University, Korea
2. School of Built Environment, Curtin University, Australia
Abstract
To optimize tower crane selection and supporting design, lifting requirements (as well as stability) should be examined, followed by a review of economic feasibility. However, construction engineers establish plans based on data provided by equipment suppliers since there are no tools with which to thoroughly examine a support design's suitability for various crane types, and such plans lack the necessary supporting data. In such cases it is impossible to optimize a tower crane selection to satisfy lifting requirements in terms of cost, and to perform lateral support and foundation design. Thus, this study is intended to develop an optimum tower crane selection and supporting design management method based on stability. All cases that are capable of generating an optimization of approximately 3,000 ˜ 15,000 times are calculated to identify the candidate cranes with minimized cost, which are examined. The optimization method developed in the study is expected to support engineers in determining the optimum lifting equipment management.
Subject
Artificial Intelligence,Computer Science Applications,Software
Cited by
14 articles.
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