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Carrillo, P and Heavey, I (2000) UK contractors’ acquisitions strategy for Central and Eastern Europe. Engineering, Construction and Architectural Management, 7(03), 322–8.

Griffith, A (2000) Integrated management systems: a single management system solution for project control?. Engineering, Construction and Architectural Management, 7(03), 232–40.

Lahdenperä, P and Tanhuanpää, V-P (2000) Creation of a new design management system based on process optimization and proactive strategy. Engineering, Construction and Architectural Management, 7(03), 267–77.

Lam, K C, Ng, S T, Hu, T, Skitmore, M R and Cheung, S-O (2000) Decision support system for contractor pre-qualification—artificial neural network model. Engineering, Construction and Architectural Management, 7(03), 251–66.

  • Type: Journal Article
  • Keywords: artificial neural network; conjugated gradient descent algorithm; contractor pre-qualification; decision support system
  • ISBN/ISSN: 0969-9988
  • URL: http://www.ingentaconnect.com/content/bsc/ecam/2000/00000007/00000003/art00156
  • Abstract:
    The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated non-linear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and 88 hypothetical pre-qualification cases were also generated according to the 'If-then' rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors' attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the 're-sampling' of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated non-linear relationship between contractors' attributes and their corresponding pre-qualification (disqualification) decision. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.

Li, H, Love, P E D and Drew, D S (2000) Effects of overtime work and additional resources on project cost and quality. Engineering, Construction and Architectural Management, 7(03), 211–20.

Nicholas, J, Holt, G D and Mihsein, M (2000) Forecasting construction materials suppliers’ financial turnover. Engineering, Construction and Architectural Management, 7(03), 221–31.

Ofori, G and Chan, S L (2000) Growth paths of construction enterprises in Singapore, 1980–98. Engineering, Construction and Architectural Management, 7(03), 307–21.

Palaneeswaran, E and Kumaraswamy, M M (2000) Benchmarking contractor selection practices in public-sector construction—a proposed model. Engineering, Construction and Architectural Management, 7(03), 285–99.

Sarshar, M, Haigh, R, Finnemore, M, Aouad, G F, Barrett, P, Baldry, D and Sexton, M (2000) SPICE: a business process diagnostics tool for construction projects. Engineering, Construction and Architectural Management, 7(03), 241–50.

Walker, D H T and Vines, M W (2000) Australian multi-unit residential project construction time performance factors. Engineering, Construction and Architectural Management, 7(03), 278–84.

Woodhead, R M and Male, S P (2000) The conditioning effect of objective decision-making on the client's capital proposal. Engineering, Construction and Architectural Management, 7(03), 300–6.