Modeling uncertain activity duration by fuzzy number and discrete-event simulation

Hong Zhang, C. M. Tam, Heng Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

39 Citations (Scopus)


This paper introduces how to incorporate fuzzy set theory and a fuzzy ranking measure with discrete-event simulation in order to model uncertain activity duration in simulating a real-world system, especially when insufficient or no sample data are available. Fuzzy numbers are used to describe uncertain activity durations, reflecting vagueness, imprecision and subjectivity in the estimation of them. A fuzzy ranking measure is merged with an activity scanning simulation algorithm for performing 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.
Original languageEnglish
Pages (from-to)715-729
Number of pages15
JournalEuropean Journal of Operational Research
Issue number3 SPEC. ISS.
Publication statusPublished - 1 Aug 2005


  • Discrete-event simulation
  • Fuzzy number
  • Fuzzy ranking
  • Fuzzy sets theory
  • Uncertainty activity duration

ASJC Scopus subject areas

  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


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