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Reactive Scheduling Systems

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Part of the book series: Operations Research / Computer Science Interfaces Series ((ORCS,volume 3))

Abstract

In most practical environments, scheduling is an ongoing reactive process where evolving and changing circumstances continually force reconsideration and revision of pre-established plans. Scheduling research has traditionally ignored this “process view” of the problem, focusing instead on optimization of performance under idealized assumptions of environmental stability and solution executability. In this paper, we present work aimed at the development of reactive scheduling systems, which approach scheduling as a problem of maintaining a prescriptive solution over time, and emphasize objectives (e.g., solution continuity, system responsiveness) which relate directly to effective development and use of schedules in dynamic environments. We describe OPIS, a scheduling system designed to incrementally revise schedules in response to changes to solution constraints. OPIS implements a constraint-directed approach to reactive scheduling. Constraint analysis is used to prioritize outstanding problems in the current schedule, identify important modification goals, and estimate the possibilities for efficient and non-disruptive schedule modification. This information, in turn, provides a basis for selecting among a set of alternative modification actions, which differ in conflict resolution and schedule improvement capabilities, computational requirements and expected disruptive effects.

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© 1995 Springer Science+Business Media New York

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Smith, S.F. (1995). Reactive Scheduling Systems. In: Brown, D.E., Scherer, W.T. (eds) Intelligent Scheduling Systems. Operations Research / Computer Science Interfaces Series, vol 3. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2263-8_7

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  • DOI: https://doi.org/10.1007/978-1-4615-2263-8_7

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-5954-8

  • Online ISBN: 978-1-4615-2263-8

  • eBook Packages: Springer Book Archive

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