Risk cost estimation of job shop scheduling with random machine breakdowns
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- @Article{WU:2019:procir,
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author = "Zigao Wu and Shudong Sun",
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title = "Risk cost estimation of job shop scheduling with
random machine breakdowns",
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journal = "Procedia CIRP",
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volume = "83",
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pages = "404--409",
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year = "2019",
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note = "11th CIRP Conference on Industrial Product-Service
Systems",
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ISSN = "2212-8271",
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DOI = "doi:10.1016/j.procir.2019.04.087",
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URL = "http://www.sciencedirect.com/science/article/pii/S2212827119307012",
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keywords = "genetic algorithms, genetic programming, scheduling,
risk cost, job shop, machine breakdowns",
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abstract = "Scheduling has been playing an important role in the
manufacturing phase of product life cycle. In this
paper, we focus on the estimation of risk cost for the
job shop scheduling under random machine breakdowns, in
which all jobs should be delivered together at a given
due date. The risk cost measures the sum of expected
earliness and tardiness costs. Considering that the
risk cost in the form of expectation does not allow
analytical calculation for the job shop scheduling, we
will try to build a computable analytical approximation
to replace the commonly used but time-consuming Monte
Carlo simulation. However, the manual design of an
effective analytical approximation is generally very
complicated. To address it, we will develop a learning
method based on the symbolic regression to extract an
analytical approximation of risk cost from experimental
data automatically. For this purpose, we first list all
the features which may be related to the risk cost by
analyzing deeply the job shop scheduling under random
machine breakdowns. Then, a learning algorithm based on
the genetic programming is proposed to extract an
analytical approximation of risk cost. Finally,
extensive experiments have shown that the accuracy of
the generated analytical approximation in evaluating
the risk cost is close to that of the Monte Carlo
simulation, while it can significantly improve the
efficiency of estimation",
- }
Genetic Programming entries for
Zigao Wu
Shudong Sun
Citations