University of Cambridge > Mathematics > Statistical Laboratory > Richard Weber > Research interests

Stochastic Scheduling

Stochastic scheduling is concerned with scheduling problems in which the processing times of tasks are modelled as random variables. Thus a job's processing time is not known until it is complete. Scheduling may be preemptive or non-preemptive, occur on one or on many processors, and be concerned with various optimization criteria.

A typical result in this area is that if n jobs have processing times that are exponentially distributed with different means and are to be processed by m identical machines operating in parallel, then LEPT (longest expected processing time first) minimizes the expected makespan (the time at which all jobs are complete.)

Database of Papers for Stochastic Scheduling

Here are some BibTeX databases for 343 papers related to stochastic scheduling. (However, they omit recent papers.)

  • Single machine models (111) updated 3 December, 1994
  • Multi-server models (101) updated 22 February, 1995
  • Gittins index (22) updated 3 December, 1994
  • Stochastic ordering (33) updated 3 December, 1994
  • Tandem queues (37) updated 3 December, 1994
  • Routing models (12) updated 3 December, 1994
  • General literature, books, etc (27) updated 22 February, 1995

  • Some macros needed to process the above files with BibTeX updated 3 December, 1994

    University of Cambridge > Mathematics > Statistical Laboratory > Richard Weber > Research interests