Anticipation and flexibility in dynamic scheduling

Anticipation and flexibility in dynamic scheduling

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Article ID: iaor200692
Country: United Kingdom
Volume: 43
Issue: 15
Start Page Number: 3103
End Page Number: 3129
Publication Date: Jan 2005
Journal: International Journal of Production Research
Authors: ,
Keywords: evolutionary algorithms
Abstract:

Many real-world optimization problems change over time and require frequent re-optimization. We suggest that in such environments, an optimization algorithm should reflect the problem's dynamics and explicitly take into account that changes to the current solution are to be expected. We claim that this can be achieved by having the optimization algorithm search for solutions that are not only good, but also flexible, i.e. easily adjustable if necessary in the case of problem changes. For the example of a job-shop with jobs arriving non-deterministically over time, we demonstrate that avoiding early idle times increases flexibility, and thus that the incorporation of an early idle time penalty as secondary objective into the scheduling algorithm can greatly enhance the overall system performance.

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