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Caldas, C H, Chou, C-C and O'Connor, J (2008) Negotiation-based decision support model for utility relocations in transportation infrastructure projects. Construction Management and Economics, 26(10), 90.

Clarke, L and Gribling, M (2008) Obstacles to diversity in construction: the example of Heathrow Terminal 5. Construction Management and Economics, 26(10), 65.

Harty, C (2008) Implementing innovation in construction: contexts, relative boundedness and actor-network theory. Construction Management and Economics, 26(10), 41.

Höök, M and Stehn, L (2008) Applicability of lean principles and practices in industrialized housing production. Construction Management and Economics, 26(10), 100.

Leiringer, R and Cardellino, P (2008) Tales of the expected: investigating the rhetorical strategies of innovation champions. Construction Management and Economics, 26(10), 54.

Lingard, H C, Townsend, K, Bradley, L and Brown, K (2008) Alternative work schedule interventions in the Australian construction industry: a comparative case study analysis. Construction Management and Economics, 26(10), 12.

Marzouk, M, Madany, M, Abou-Zied, A and El-said, M (2008) Handling construction pollutions using multi-objective optimization. Construction Management and Economics, 26(10), 25.

  • Type: Journal Article
  • Keywords: built environment; genetic algorithms; optimization techniques
  • ISBN/ISSN: 0144-6193
  • URL: https://doi.org/10.1080/01446190802400779
  • Abstract:
    Quantitative assessment of emissions associated with construction projects should be carried out during the planning phase of the projects. This is important to detect and highlight any excesses of residuals during the construction phase. A newly developed framework is proposed to handle construction pollution using multi-objective optimization. The approach, utilized by the proposed framework, is based on calculating the generated pollution for each activity involved in the project, as a result of dust, harmful gases and noise. The results of the quantitative assessment are integrated in a utility function that expresses the amount of total pollution. Then, evolutionary genetic algorithms (GAs) are used to carry multi-objective optimization, considering three objective functions (project duration, project cost and total pollution). The proposed application considers the dynamic nature of construction activities including different types of relationships and the change of activities' criticality. An actual case study is worked out to demonstrate the practical use of the proposed framework and to investigate the sensitivity of its parameters.

Pan, W, Gibb, A G F and Sellars, A B (2008) Maintenance cost implications of utilizing bathroom modules manufactured offsite. Construction Management and Economics, 26(10), 77.

Zhang, X, Austin, S, Glass, J and Mills, G (2008) Toward collective organizational values: a case study in UK construction. Construction Management and Economics, 26(10), 28.