Genetic Programming for Evolving Due-date Assignment Models in Job Shop Environments
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{Nguyen:2013:EC,
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author = "Su Nguyen and Mengjie Zhang and Mark Johnston and
Kay Chen Tan",
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title = "Genetic Programming for Evolving Due-date Assignment
Models in Job Shop Environments",
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journal = "Evolutionary Computation",
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year = "2014",
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volume = "22",
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number = "1",
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pages = "105--138",
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month = "Spring",
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keywords = "genetic algorithms, genetic programming, job shop,
due-date assignment, hyper-heuristics",
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ISSN = "1063-6560",
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URL = "http://www.mitpressjournals.org/doi/pdf/10.1162/EVCO_a_00105",
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DOI = "doi:10.1162/EVCO_a_00105",
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size = "27 pages",
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abstract = "Due-date assignment plays an important role in
scheduling systems and strongly influences the delivery
performance of job shops. Because of the stochastic and
dynamic nature of job shops, the development of general
due-date assignment models (DDAMs) is complicated. In
this study, two genetic programming (GP) methods are
proposed to evolve DDAMs for job shop environments. The
experimental results show that the evolved DDAMs can
make more accurate estimates than other existing
dynamic DDAMs with promising reusability. In addition,
the evolved operation-based DDAMs show better
performance than the evolved DDAMs employing aggregate
information of jobs and machines.",
- }
Genetic Programming entries for
Su Nguyen
Mengjie Zhang
Mark Johnston
Kay Chen Tan
Citations