TECHNICAL PAPERS
Apr 10, 2010

Application of a SOM-Based Optimization Algorithm in Minimizing Construction Time for Secant Pile Wall

Publication: Journal of Construction Engineering and Management
Volume 136, Issue 11

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.

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Published In

Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 136Issue 11November 2010
Pages: 1189 - 1195

History

Received: Feb 6, 2009
Accepted: Apr 7, 2010
Published online: Apr 10, 2010
Published in print: Nov 2010

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Authors

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Jieh-Haur Chen [email protected]
Associate Professor, Grad. Inst. of Construction Engineering and Management, National Central Univ., 300 Jhongda, Jhongli, Taoyuan 32001, Taiwan. E-mail: [email protected]
Professor, Dept. of Computer Science and Information Engineering, National Central Univ., 300 Jhongda, Jhongli, Taoyuan 32001, Taiwan. E-mail: [email protected]
De-Yuan Huang [email protected]
Ph.D. Student, Dept. of Computer Science and Information Engineering, National Central Univ., 300 Jhongda, Jhongli, Taoyuan 32001, Taiwan. E-mail: [email protected]

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