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. (As yet, these are not yet fully up-to-date for the last few years.)

Please tell me if you use this database or think you might find it useful.

If you would like to add to, correct, or make suggestions for better organization of this database, please send email to r.r.weber@statslab.cam.ac.uk

  • 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

  • People who have helped contribute to this database.

    Richard Weber's publication list and home page