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Using fuzzy logic theory to improve construction productivity

Mortaheb, M. M ; Sharif University of Technology | 2008

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  1. Type of Document: Article
  2. Publisher: 2008
  3. Abstract:
  4. Fuzzy logic is a powerful problem-solving methodology that provides a remarkably simple way to draw definite conclusions from vague, ambiguous or imprecise information. This study is a review on the possibility of developing a tool to help site managers and planners in selecting the most suitable actions for construction productivity improvement in a complex construction site, using fuzzy logic theory. Improving productivity can have a large impact on the overall construction process and consequently result in significant time and cost savings, i.e. minimizing capital cost on the construction projects. Problems associated with productivity measurement such as "lack of a standard productivity measurement method and guidelines" as well as "difficulties facing productivity quantification" justifies the need for developing innovative methods or tools such as the fuzzy decision support system in order to improve construction productivity. This application of fuzzy logic theory is a step towards the elimination of bias or prejudice in the judgment of an expert, since the steps leading to the judgment are made explicit
  5. Keywords:
  6. Capital costs ; Complex constructions ; Construction process ; Construction productivities ; Construction projects ; Cost savings ; Fuzzy decision support systems ; Fuzzy logic theories ; Imprecise informations ; Innovative methods ; Problem-solving ; Productivity measurement methods ; Productivity measurements ; Site managers ; Artificial intelligence ; Civil engineering ; Construction industry ; Decision support systems ; Decision theory ; Fuzzy sets ; Innovation ; Productivity ; Standardization ; Fuzzy logic
  7. Source: Proceedings, Annual Conference - Canadian Society for Civil Engineering, 10 June 2008 through 13 June 2008, Quebec City, QC ; Volume 1 , 2008 , Pages 585-596 ; 9781605603964 (ISBN)
  8. URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-63049128015&partnerID=40&md5=cbd72f0b88257cd4215a44dba85afada