Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.
Civil Infrastructure assets require continuous renewal
actions to sustain their operability and safety. Allocating
limited renewal funds amongst numerous building
components, however, represents a large-scale
optimization problem and earlier efforts utilized genetic
algorithms (GAs) to optimize medium size problems yet
exhibit steep performance degradation as problem size
increases. In this research, after experimenting with
various approaches of segmenting a large problem into
multiple smaller sub-problems, clustered segmentation
proved to be the most promising. The paper discusses the
underlying life cycle analysis model, the various
segmentation methods, and the optimization results using
the improved GAs + clustered segmentation, which
proved to be able to optimize asset renewals for 50,000
components with no noticeable performance degradation.
The proposed method is simple and logical, and can be
used on variety of asset types to improve infrastructure
fund allocation. Future extension of this research is then
highlighted.