Evaluating Online Scheduling Techniques in Uncertain Environments
نویسندگان
چکیده
Online scheduling (also known as dynamic scheduling) refers to the real-time coordination of operation processing while new operations are continuously arriving. The objective of this paper is the study of different online scheduling techniques in a dynamic, stochastic job shop scheduling environment. We present a quantitative study of the quality of dispatching and optimizing scheduling techniques under varying uncertainty and utilization. Therein, we also consider a regret-based algorithm adopted from Bent and Van Hentenryck [1] in a setting with stochastic processing times and analyze its performance. To date, results in such a dynamic setting are lacking, while it has been shown to outperform other heuristic optimization methods in online packet scheduling with processing times known a priori.
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