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Journal of Scheduling

, Volume 7, Issue 4, pp 277–292 | Cite as

Predictive, Stochastic and Dynamic Extensions to Aversion Dynamics Scheduling

  • Gary W. BlackEmail author
  • Kenneth N. McKay
  • Sherri L. Messimer
Article

Abstract

Schedulers' decisions in real factories deal with perceived risks and impacts. They proactively anticipate and reactively mitigate risky events by altering what would be considered a normal schedule to minimize associated impacts. These risk mitigation concepts are called aversion dynamics (AD). Aversion dynamics describes the aversion that jobs exhibit to impacts resulting from risky events in dynamic and unstable production environments. The aversion manifests itself in either advancing or delaying the work to avoid the risky period. This paper extends the first AD heuristic, Averse-1, to capture additional real-world dynamics and to make the heuristic predictive (proactive) as to when the perceived risky event may happen. In particular, predictive and stochastic elements are incorporated within a dynamic job arrival framework to create an extended heuristic called Averse-2.

aversion dynamics adaptive heuristics rescheduling robust scheduling 

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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Gary W. Black
    • 1
    Email author
  • Kenneth N. McKay
    • 2
  • Sherri L. Messimer
    • 3
  1. 1.Faculty of Industrial & Manufacturing EngineeringTennessee Technological UniversityCookevilleUSA
  2. 2.Department of Management SciencesUniversity of WaterlooWaterlooCanada
  3. 3.Faculty of Industrial & Systems Engineering and Engineering ManagementUniversity of Alabama in HuntsvilleHuntsvilleUSA

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