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Ammar, M A (2011) Optimization of Project Time-Cost Trade-Off Problem with Discounted Cash Flows. Journal of Construction Engineering and Management, 137(01), 65–71.

Gull, I (2011) Testing of Strength of Recycled Waste Concrete and Its Applicability. Journal of Construction Engineering and Management, 137(01), 1–5.

Hariga, M and El-Sayegh, S M (2011) Cost Optimization Model for the Multiresource Leveling Problem with Allowed Activity Splitting. Journal of Construction Engineering and Management, 137(01), 56–64.

Hassan, M M, Odeh, I and El-Rayes, K (2011) New Approach to Compare Glare and Light Characteristics of Conventional and Balloon Lighting Systems. Journal of Construction Engineering and Management, 137(01), 39–44.

Lucko, G (2011) Integrating Efficient Resource Optimization and Linear Schedule Analysis with Singularity Functions. Journal of Construction Engineering and Management, 137(01), 45–55.

Mitropoulos, P and Namboodiri, M (2011) New Method for Measuring the Safety Risk of Construction Activities: Task Demand Assessment. Journal of Construction Engineering and Management, 137(01), 30–38.

Rashidi, A, Jazebi, F and Brilakis, I (2011) Neurofuzzy Genetic System for Selection of Construction Project Managers. Journal of Construction Engineering and Management, 137(01), 17–29.

  • Type: Journal Article
  • Keywords: Construction management; Managers; Fuzzy sets; Parameters; Recruiting; Construction project manager; Selection criteria; Fuzzy system; Parameter identification;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000200
  • Abstract:
    Choosing a project manager for a construction project—particularly, large projects—is a critical project decision. The selection process involves different criteria and should be in accordance with company policies and project specifications. Traditionally, potential candidates are interviewed and the most qualified are selected in compliance with company priorities and project conditions. Precise computing models that could take various candidates’ information into consideration and then pinpoint the most qualified person with a high degree of accuracy would be beneficial. On the basis of the opinions of experienced construction company managers, this paper, through presenting a fuzzy system, identifies the important criteria in selecting a project manager. The proposed fuzzy system is based on IF-THEN rules; a genetic algorithm improves the overall accuracy as well as the functions used by the fuzzy system to make initial estimates of the cluster centers for fuzzy c-means clustering. Moreover, a back-propagation neutral network method was used to train the system. The optimal measures of the inference parameters were identified by calculating the system’s output error and propagating this error within the system. After specifying the system parameters, the membership function parameters—which by means of clustering and projection were approximated—were tuned with the genetic algorithm. Results from this system in selecting project managers show its high capability in making high-quality personnel predictions.

Regan, M, Smith, J and Love, P E D (2011) Impact of the Capital Market Collapse on Public-Private Partnership Infrastructure Projects. Journal of Construction Engineering and Management, 137(01), 6–16.

Shen, X, Lu, M and Chen, W (2011) Tunnel-Boring Machine Positioning during Microtunneling Operations through Integrating Automated Data Collection with Real-Time Computing. Journal of Construction Engineering and Management, 137(01), 72–85.

Zhou, Q, Fang, D and Mohamed, S (2011) Safety Climate Improvement: Case Study in a Chinese Construction Company. Journal of Construction Engineering and Management, 137(01), 86–95.