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Dynamic single-machine scheduling under distributed decision-making
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DOI：10.1080/00207540050175996.png)
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Abstract
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This paper presents a deterministic dynamic model for the single-machine scheduling problem. The model uses forecasts of future job arrivals with the current data to extract job interactions over time, updating the information on rolling basis. The model is implemented in a distributed structure with both the machine and the jobs involved in decision-making to create a schedule. The decision-making is modelled similar to an auction with a theoretical basis for problem decomposition, bid construction and bid evaluation. Numerical results indicate that the model outperforms other distributed implementations in both static and dynamic implementations for a wide range of single-machine scheduling problems.
Keywords:
TARDINESS PENALTIES
MANUFACTURING SYSTEMS
ABSOLUTE DEVIATION
COMPLETION TIMES
EARLINESS
COMMON
DATE
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