One machine scheduling problem with fuzzy random due-dates

Takeshi Itoh, Hiroaki Ishii

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


In many classical or basic scheduling models, jobs' processing times and due-dates are crisp values. Recently, they have been formulated as uncertain values in some more actual models. That is the introduction of "fuzziness". However, in a real situation of decision making, there exists uncertainty that can not be described only by fuzziness. In this paper, we propose an n-job, one machine scheduling model, where due-dates for jobs are fuzzy random variables. In the model, jobs' processing times are crisp, and we assign satisfaction levels to jobs' completion times according to membership functions. They are non-increasing functions, but their support positions depend upon the expected due-dates, which are exponentially distributed random variables.

Original languageEnglish
Pages (from-to)71-78
Number of pages8
JournalFuzzy Optimization and Decision Making
Issue number1
Publication statusPublished - 2005 Feb
Externally publishedYes


  • Binary search
  • Exponential distribution
  • Fuzzy random variable
  • One machine scheduling

ASJC Scopus subject areas

  • Software
  • Logic
  • Artificial Intelligence


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