An expert system for dynamic scheduling

  • Authors:

  • D Ford;S Floyd

  • Affiliations:

  • The Artificial Intelligence Laboratory, Johnson Research Center, University of Alabama, Huntsville, Huntsville, AL;The Artificial Intelligence Laboratory, Johnson Research Center, University of Alabama, Huntsville, Huntsville, AL

  • Venue:
  • ISMIS '86 Proceedings of the ACM SIGART international symposium on Methodologies for intelligent systems
  • Year:
  • 1986

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Abstract

Traditionally, scheduling problems have been viewed as static in nature (i.e., a schedule is developed for a particular planning horizon and adhered to) and were cast as having one or more clearly defined objectives (e.g., minimize overall completion time, maximize resource utilization, etc.). These problems were most commonly solved via application of optimal seeking algorithms, heuristics or simulation analysis [1] [5] [9] [10] [17]. The payload scheduling problem is representative of a class of scheduling problems which are highly dynamic in nature. That is, the various parameters can change at any time, and the objectives themselves may change also. The nature of this class of problems is such that they can be most effectively solved by knowledge based expert systems [2] [3] [8] [13] [19] [20].