Neuro-Fuzzy Cost Estimation Model Enhanced by Fast Messy Genetic Algorithms for Semiconductor Hookup Construction

:  Semiconductor hookup construction (i.e., constructing process tool piping systems) is critical to semiconductor fabrication plant completion. During the conceptual project phase, it is difficult to conduct an accurate cost estimate due to the great amount of uncertain cost items. This study propo...

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Bibliographic Details
Published in:Computer-aided civil and infrastructure engineering 2012-11, Vol.27 (10), p.764-781
Main Authors: Hsiao, Fan-Yi, Wang, Shih-Hsu, Wang, Wei-Chih, Wen, Chao-Pao, Yu, Wen-Der
Format: Article
Language:English
Subjects:
Applied sciences
Building economics. Cost
Buildings
Buildings. Public works
Computation methods. Tables. Charts
Construction costs
Construction equipment
Cost engineering
Cost estimates
Exact sciences and technology
Fuzzy logic
Genetic algorithms
Industrial facility (building, storage, etc.)
Marketing
Semiconductors
Structural analysis. Stresses
Types of buildings
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Summary::  Semiconductor hookup construction (i.e., constructing process tool piping systems) is critical to semiconductor fabrication plant completion. During the conceptual project phase, it is difficult to conduct an accurate cost estimate due to the great amount of uncertain cost items. This study proposes a new model for estimating semiconductor hookup construction project costs. The developed model, called FALCON‐COST, integrates the component ratios method, fuzzy adaptive learning control network (FALCON), fast messy genetic algorithm (fmGA), and three‐point cost estimation method to systematically deal with a cost‐estimating environment involving limited and uncertain data. In addition, the proposed model improves the current FALCON by devising a new algorithm to conduct building block selection and random gene deletion so that fmGA operations can be implemented in FALCON. The results of 54 case studies demonstrate that the proposed model has estimation accuracy of 83.82%, meaning it is approximately 22.74%, 23.08%, and 21.95% more accurate than the conventional average cost method, component ratios method, and modified FALCON‐COST method, respectively. Providing project managers with reliable cost estimates is essential for effectively controlling project costs.
ISSN:1093-9687
1467-8667
DOI:10.1111/j.1467-8667.2012.00786.x