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Ison, S, Dainty, A and Wall, S (2004) The construction sector, congestion charging and exemptions. Engineering, Construction and Architectural Management, 11(06), 386–94.

Liu, A M M, Fellows, R and Ng, J (2004) Surveyors' perspectives on ethics in organisational culture. Engineering, Construction and Architectural Management, 11(06), 438–49.

Nguyen, L D, Ogunlana, S O and Lan, D T X (2004) A study on project success factors in large construction projects in Vietnam. Engineering, Construction and Architectural Management, 11(06), 404–13.

Soetanto, R, Dainty, A R J, Glass, J and Price, A D F (2004) Criteria for assessing the potential performance of hybrid concrete structural frames. Engineering, Construction and Architectural Management, 11(06), 414–25.

Wibowo, A (2004) Valuing guarantees in a BOT infrastructure project. Engineering, Construction and Architectural Management, 11(06), 395–403.

Zhang, H, Li, H and Tam, C M (2004) Fuzzy discrete-event simulation for modeling uncertain activity duration. Engineering, Construction and Architectural Management, 11(06), 426–37.

  • Type: Journal Article
  • Keywords: construction industry; fuzzy logic; simulation
  • ISBN/ISSN: 0969-9988
  • URL: http://dandini.emeraldinsight.com/vl=1462875/cl=137/nw=1/rpsv/cw/mcb/09699988/v11n6/s5/p426
  • Abstract:
    Construction-oriented discrete-event simulation often faces the problem of defining uncertain information input, such as subjectivity in selecting probability distributions that result from insufficient or lack of site productivity data. This paper proposes incorporation of fuzzy set theory with discrete-event simulation to handle the vagueness, imprecision and subjectivity in the estimation of activity duration, especially when insufficient or no sample data are available. Based upon an improved activity scanning simulation algorithm, a fuzzy distance ranking measure is adopted in fuzzy simulation time advancement and event selection for simulation experimentation. The uses of the fuzzy activity duration and the probability distribution-modeled duration are compared through a series of simulation experiments. It is observed that the fuzzy simulation outputs are arrived at through only one cycle of fuzzy discrete-event simulation, still they contain all the statistical information that are produced through multiple cycles of simulation experiments when the probability distribution approach is adopted.