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Potentialities of a Highway Alignment Optimization Method in an I-BIM Environment.
- Source :
-
Periodica Polytechnica: Civil Engineering . 2019, Vol. 63 Issue 2, p352-361. 10p. - Publication Year :
- 2019
-
Abstract
- The BIM (Building Information Modeling) approach potential in the civil engineering field opened novel scenarios in the design idea concept, from planning to executive and constructive phases. The related advantages are numerous and not only limited to a realtime interaction among the involved subjects, that can actually operate in an optimized 3D shared environment. Owing to the sharing information philosophy and to the features of various "smart objects" combined in the project, this innovation reduces potential errors and increases the effectiveness of the design solution in terms of both functionality and cost. Despite these advantages, the highway alignment design problem remains very complicated and not easy to solve without appropriate supporting tools. In recent years, several efforts have been spent in defining highway optimization procedures for helping designers in the selection of an optimal solution in compliance with numerous different constraints. Introducing these procedures in a BIM environment may represent a crucial step in the improvement of the highway design procedures, exploiting the full representation and modelling potential of the approach. In this paper, the authors present the advantages of a 3D highway alignment optimization algorithm, based on the Particle Swarm Optimization method, and its possible implementation in a BIM platform. A proper I-BIM environment can exploit the potential of the alignment optimization algorithms, simplifying the analysis of the different solutions, the final representation and the eventual manual modifications. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 05536626
- Volume :
- 63
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Periodica Polytechnica: Civil Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 136780288
- Full Text :
- https://doi.org/10.3311/PPci.12220