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Abeid, J and Arditi, D (2002) Time-Lapse Digital Photography Applied to Project Management. Journal of Construction Engineering and Management, 128(06), 530–5.

Arditi, D, Tokdemir, O B and Suh, K (2002) Challenges in Line-of-Balance Scheduling. Journal of Construction Engineering and Management, 128(06), 545–56.

Ariaratnam, S T and MacLeod, C W (2002) Financial Outlay Modeling for a Local Sewer Rehabilitation Strategy. Journal of Construction Engineering and Management, 128(06), 486–95.

Chan, W T and Hu, H (2002) Constraint Programming Approach to Precast Production Scheduling. Journal of Construction Engineering and Management, 128(06), 513–21.

del Caño, A and de la Cruz, M P (2002) Integrated Methodology for Project Risk Management. Journal of Construction Engineering and Management, 128(06), 473–85.

Goodrum, P M and Haas, C T (2002) Partial Factor Productivity and Equipment Technology Change at Activity Level in U.S. Construction Industry. Journal of Construction Engineering and Management, 128(06), 463–72.

Kashiwagi, D T and Byfield, R (2002) Testing of Minimization of Subjectivity in Best Value Procurement by Using Artificial Intelligence Systems in State of Utah Procurement. Journal of Construction Engineering and Management, 128(06), 496–502.

  • Type: Journal Article
  • Keywords: Construction; Artificial intelligence; Utah; Cost control; Project management; artificial intelligence; construction industry; cost optimal control; project management; civil engineering;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2002)128:6(496)
  • Abstract:
    The Performance Information Procurement System (PIPS) was tested on the procurement of the $2.96 million Bridgerland Academic Training Center (ATC) for the state of Utah Division of Facilities Construction Management. The artificial intelligence (AI) information based PIPS was run two ways—selection with biased subjectivity (similar to current best value processes) and without biased subjectivity. Unlike other best value processes, PIPS minimizes the decision-making and subjective bias of the owner’s representatives. The procurement test at Bridgerland ATC provides a comparison between the AI selection versus the user agency’s subjective prioritization. The result of the system was one of the “best” construction projects procured at the state of Utah (on time, on budget, high quality), with no contractor generated change orders for additional cost, minimized construction management requirements, and high customer satisfaction.

Knight, K and Robinson Fayek, A (2002) Use of Fuzzy Logic for Predicting Design Cost Overruns on Building Projects. Journal of Construction Engineering and Management, 128(06), 503–12.

Maloney, W F (2002) Construction Product/Service and Customer Satisfaction. Journal of Construction Engineering and Management, 128(06), 522–9.

Peng, J (2002) Stability Analyses and Design Recommendations for Practical Shoring Systems during Construction. Journal of Construction Engineering and Management, 128(06), 536–44.