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A decision support system for substage-zoning filling design of rock-fill dams based on particle swarm optimization

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Abstract

In this paper, we studied a substage-zoning filling design problem, which is considered as a complex problem with numerous tasks such as construction planning, dam access road and borrow placement, workspace filling, and construction project management. In analyzing workflows and the mechanism of substage-zoning filling, not only the above-mentioned tasks are considered, but also the environmental factors such as rainfall and hydrology characteristic temperature are taken into account. In this study, an optimization model for dam filling which aimed at reducing the disequilibrium degree of filling intensity was proposed; in addition, a technique based on particle swarm optimization was introduced as the basis of a decision support system for rock-fill dams. The system has been employed in a water conservancy and hydropower project which shows that the system is able to provide quality decision support and facilitate the rock-fill dam construction effectively.

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Acknowledgments

The authors acknowledge the support of the National Natural Science Foundation of China (Grant No 70971005), the Ministry of Science and Technology of China (Grant No 2006BAK04A23), Quality Inspection Project: Current State Analysis and Strategy Research about Consumer Products on Inspection and Testing Methods (Grant No 200910088) and Changjiang Scholars Program of the Ministry of Education of China.

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Authors and Affiliations

  1. School of Economics and Management, Beihang University, Xue Yuan Road No. 37, HaiDian District, Beijing, 100191, China

    Li Wang & Junwei Zeng

  2. Jilin University, Changchun, 130023, China

    Li Xu

  3. University of Science and Technology of China, Hefei, 230026, China

    Li Xu

Authors
  1. Li Wang
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  2. Junwei Zeng
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  3. Li Xu
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Correspondence to Junwei Zeng.

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Wang, L., Zeng, J. & Xu, L. A decision support system for substage-zoning filling design of rock-fill dams based on particle swarm optimization. Inf Technol Manag 12, 111–119 (2011). https://doi.org/10.1007/s10799-011-0092-7

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  • DOI: https://doi.org/10.1007/s10799-011-0092-7

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