On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems
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- @Article{CHAND:2018:IS,
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author = "Shelvin Chand and Quang Huynh and Hemant Singh and
Tapabrata Ray and Markus Wagner",
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title = "On the use of genetic programming to evolve priority
rules for resource constrained project scheduling
problems",
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journal = "Information Sciences",
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volume = "432",
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pages = "146--163",
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year = "2018",
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keywords = "genetic algorithms, genetic programming, Resource
constrained project scheduling, Heuristic evolution,
Evolutionary computation, Generation hyper-heuristics",
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ISSN = "0020-0255",
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DOI = "doi:10.1016/j.ins.2017.12.013",
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URL = "http://www.sciencedirect.com/science/article/pii/S0020025517311350",
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abstract = "Resource constrained project scheduling is critical in
logistic and planning operations across a range of
industries. Most businesses rely on priority rules to
determine the order in which the activities required
for the project should be executed. However, the design
of such rules is non-trivial. Even with significant
knowledge and experience, human experts are
understandably limited in terms of the possibilities
they can consider. This paper introduces a genetic
programming based hyper-heuristic (GPHH) for producing
efficient priority rules targeting the resource
constrained project scheduling problem (RCPSP). For
performance analysis of the proposed approach, a series
of experiments are conducted on the standard PSPLib
instances with up to 120 activities. The evolved
priority rules are then compared against the existing
state-of-the-art priority rules to demonstrate the
efficacy of our approach. The experimental results
indicate that our GPHH is capable of producing reusable
priority rules which significantly out-perform the best
human designed priority rules",
- }
Genetic Programming entries for
Shelvin Chand
Quang Nhat Huynh
Hemant Singh
Tapabrata Ray
Markus Wagner
Citations