Learning the Distribution Characteristics of Critical Machines in Production Scheduling Problems

Rui Zhang

doi:10.4028/www.scientific.net/AMR.337.142

Paper Titles

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Learning the Distribution Characteristics of Critical Machines in Production Scheduling Problems
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The Synthesis of Novel Chiral Organic Light-Emitting Material: 2R,3R-Di(tert-Butanesulfiny)Thiophene
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 337Learning the Distribution Characteristics of...

Learning the Distribution Characteristics of Critical Machines in Production Scheduling Problems

Abstract:

A critical machine identification algorithm is proposed for the job shop scheduling problem in which the total tardiness must be minimized. An optimization-based procedure is devised to learn the distribution characteristics of critical machines in a specific scheduling instance. The proposed simulated annealing algorithm optimizes the scheduling problem after the capacity constraints for each machine are modified. A genetic algorithm based on combined dispatching rules is designed to verify the effectiveness of the proposed methodology.

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Materials Processing Technology, ICMPMT2011

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Advanced Materials Research (Volume 337)

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142-145

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.337.142

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September 2011

Authors:

Rui Zhang

Keywords:

Critical Machine, Genetic Algorithm (GA), Production Scheduling

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References

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