MULTI-OBJECTIVE OPTIMIZATION OF SUPPORTING PLAN FOR DEEP FOUNDATION USING ENTROPY-BASED UM-DEA
DOI:
https://doi.org/10.14311/CEJ.2019.02.0023Keywords:
Deep foundation pit, Unascertained measurement evaluation, Data envelopment analysis, Information entropyAbstract
In regard to optimize the supporting plan of deep foundation pit, this paper used the unascertained measurement (UM) and data envelopment analysis (DEA) to conduct. In order to determine the relationship between influencing factors and the best bid plan, an evaluation model for deep foundation pit support schemes based on UM was developed. First, the information entropy (IE) was introduced to determine the weight of discriminant indices which consider the confidence identification criteria as the judgment principle of evaluation. Then, the optimal solution from all feasible support schemes was investigated. Finally, Fuzzy comprehension assessment- data envelopment analysis (FCA-DEA) was utilized to analyse the effectiveness of design plans, which was evaluated by UME subsequently. Applicability of the proposed UM-DEA model was tested with four real design cases of foundation projects. Results compared with other methods have shown the developed model is useful for concept design and decision making of supporting plan for deep foundation.
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References
R. L. Lu, Q. H. Jiang. Reinforcement Scheme and Numerical Simulation for Sequential Excavation of the Deep Foundation Pit. Applied Mechanics & Materials, 2012, 204-208:359-365.
J.Y. Lin, T.M. Zeng, X.G. WU, .L.M. Zhang. Safety assessment of deep foundation pit engineering based on Extenics. Material Science and Environmental Engineering, 2016: 740-749.
Horkoshi, K. And Randolph, M. F. A Contribution to optimum Design of Pi led Rafts. Geotechnique. 1998, 48(3): 301-317.
Poulos H.G. Pi led Raft Foundation: Design and Application Geotechnique. Geotechnique,2001, 51(2) : 95-113.
R. Li et al., The Technique of Deep Foundation Pit and Pile Foundation Construction, Applied Mechanics and Materials, 2012, 204-208:308-311,
Audun Jøsang. Subjective Logic: A Formalism for Reasoning Under Uncertainty. Springer, Heidelberg, 2016.
David Sundgren and Alexander Karlsson. Uncertainty levels of second-order probability. Polibits, 2013, 48:5-11.
Yang Guoliang, Liu Wenbin, Zheng Haijun. A review of the data envelopment analysis method (DEA). Journal of systems engineering, 2013,(06):840-860.
Cook, W.D., Tone, K., and Zhu, J., Data envelopment analysis: Prior to choosing a model, OMEGA, 2014, 44:1-4.
Park, B., L. Simar and V. Zelenyuk. Categorical data in local maximum likelihood: theory and applications to productivity analysis. Journal of Productivity Analysis. 2015,43(2): 199-214.
Sherman H.D, Zhu J. Analyzing performance in service organizations. Sloan Management Review. 2013, 54(4): 37-42.
Antunes, Ricardo; Gonzalez, Vicente. A Production Model for Construction: A Theoretical Framework. Buildings. 2015,5(1): 209-228.
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