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AbouRizk, S M and Halpin, D W (1992) Statistical Properties of Construction Duration Data. Journal of Construction Engineering and Management, 118(03), 525–44.

De La Garza, J M and Mitropoulos, P (1992) Flavors and Mixins of Expert Systems Technology Transfer Model for AEC Industry. Journal of Construction Engineering and Management, 118(03), 435–53.

Eldin, N N and Senouci, A B (1992) Use of Scrap Tires in Road Construction. Journal of Construction Engineering and Management, 118(03), 561–76.

Harris, R B (1992) A Challenge for Research. Journal of Construction Engineering and Management, 118(03), 422–34.

Hicks, J C (1992) Heavy Construction Estimates, with and without Computers. Journal of Construction Engineering and Management, 118(03), 545–60.

Nam, C H and Tatum, C B (1992) Government‐Industry Cooperation: Fast‐Track Concrete Innovation. Journal of Construction Engineering and Management, 118(03), 454–71.

Nam, C H and Tatum, C B (1992) Strategies for Technology Push: Lessons from Construction Innovations. Journal of Construction Engineering and Management, 118(03), 507–24.

Russell, J S and Jaselskis, E J (1992) Quantitative Study of Contractor Evaluation Programs and Their Impact. Journal of Construction Engineering and Management, 118(03), 612–24.

Shaked, O and Warszawski, A (1992) CONSCHED: Expert System for Scheduling of Modular Construction Projects. Journal of Construction Engineering and Management, 118(03), 488–506.

Skibniewski, M J and Chao, L (1992) Evaluation of Advanced Construction Technology with AHP Method. Journal of Construction Engineering and Management, 118(03), 577–93.

Thomas, H R, Smith, G R and Ponderlick, R M (1992) Resolving Contract Disputes Based on Misrepresentations. Journal of Construction Engineering and Management, 118(03), 472–87.

Tommelein, I D, Levitt, R E and Hayes‐Roth, B (1992) Site‐Layout Modeling: How Can Artificial Intelligence Help?. Journal of Construction Engineering and Management, 118(03), 594–611.

  • Type: Journal Article
  • Keywords: Artificial intelligence; Knowledge‐based systems; Expert systems; Construction management; Site preparation, construction;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(1992)118:3(594)
  • Abstract:
    Using the site‐layout task as an example to compare existing practices and tools used in industry and research environments, this paper puts artificial intelligence (AI) modeling techniques in perspective. The site‐layout task is characterized, field practice is described, and a thorough review of available tools for layout product modeling (including physical models and computer‐aided design tools) and process modeling (using AI as well as operations research methods) is presented. A rationale is provided for why many such tools have failed to gain widespread use in the construction industry. Comparing the capabilities as well as the data and knowledge needs of computer programs with those of construction practitioners reveals a large discrepancy, which is also apparent when fitting the layout literature in a comprehensive table. This paper argues that AI‐based systems can reduce this discrepancy by better matching model capabilities with industry needs, and, therefore, suggests that such models will become valuable decision‐support tools for construction management.