An Evolved Dispatching Rule Based Scheduling Approach for Solving DJSS Problem
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Xu:2021:CCC,
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author = "Binzi Xu and Liang Tao and Xiongfeng Deng and Wei Li",
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title = "An Evolved Dispatching Rule Based Scheduling Approach
for Solving DJSS Problem",
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booktitle = "2021 40th Chinese Control Conference (CCC)",
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year = "2021",
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pages = "6524--6531",
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abstract = "Dynamic job shop scheduling (DJSS) has been shown as a
realistic and complex combinatorial optimization
problem, which is characterized by complexity,
dynamics, and uncertainty. Though dispatching rules
(DRs) have been seen as a suitable method for solving
DJSS problem, it is hard to manually design a DR with
good scheduling performance considering all the
aspects, much less a general DR for the complex dynamic
environment of the job shop. This paper presents a
genetic programming hyper-heuristic (GPHH) based DR
evaluation approach to automatically generate
customized DRs, in which job shop configuration,
objective, and other information are considered. After
testing it on the single objective DJSS problems with
six different scenarios, the experimental result
indicates that the proposed method can effectively
evolve better DRs for different DJSS problems than
manually designed DRs. Besides, the role of four key
parameters in GPHH, including the number of
generations, the population size, and the maximal
depth, have been deeply analyzed based on the
corresponding experiments.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.23919/CCC52363.2021.9549754",
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ISSN = "1934-1768",
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month = jul,
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notes = "Also known as \cite{9549754}",
- }
Genetic Programming entries for
Binzi Xu
Liang Tao
Xiongfeng Deng
Wei Li
Citations