Abstract
Construction time matters for activities where rental equipment must be used. The building of a secant pile wall requires the rental of equipment and finding the optimal sequence to minimize the construction time is one way to lower construction costs. In this study we develop an effective and efficient optimization algorithm, which we call self-organizing feature map (SOM)-based optimization (SOMO), to minimize the construction time. The algorithm is applied to a case study to obtain the optimal sequences for both primary and secondary bored piles for a secant pile wall. The new SOMO algorithm is developed based on the ability of the human brain to produce topologically ordered mapping, so as to exploit better solutions via updating the weighting vectors of the neurons in a self-organizing topological way that occurs in the evolution of the feature map for optimization. Given detailed building time of the 16 activities of each bored pile, we find that 143.92 h or 27.21% of the original construction can be saved. The optimal sequences for both primary and secondary bored piles are also determined. The practicability of the SOMO algorithm is substantiated.
Original language | English |
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Pages (from-to) | 1189-1195 |
Number of pages | 7 |
Journal | Journal of Construction Engineering and Management |
Volume | 136 |
Issue number | 11 |
DOIs | |
State | Published - Nov 2010 |
Keywords
- Construction time
- Optimal sequencing
- Optimization
- Secant pile wall
- Self-organizing feature map (SOM)
- SOMO algorithm