A hyper-heuristic based ensemble genetic programming approach for stochastic resource constrained project scheduling problem
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @Article{CHEN:2021:ESA,
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author = "HaoJie Chen and Guofu Ding and Shengfeng Qin and
Jian Zhang2",
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title = "A hyper-heuristic based ensemble genetic programming
approach for stochastic resource constrained project
scheduling problem",
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journal = "Expert Systems with Applications",
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volume = "167",
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pages = "114174",
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year = "2021",
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ISSN = "0957-4174",
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DOI = "doi:10.1016/j.eswa.2020.114174",
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URL = "https://www.sciencedirect.com/science/article/pii/S0957417420309118",
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keywords = "genetic algorithms, genetic programming, Ensemble
decision, Hyper-heuristics, Priority rule, Stochastic
resource constrained project scheduling",
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abstract = "In project scheduling studies, to the best of our
knowledge, the hyper-heuristic collaborative scheduling
is first-time applied to project scheduling with random
activity durations. A hyper-heuristic based ensemble
genetic programming (HH-EGP) method is proposed for
solving stochastic resource constrained project
scheduling problem (SRCPSP) by evolving an ensemble of
priority rules (PRs). The proposed approach features
with (1) integrating the critical path method into the
resource-based policy class to generate schedules; (2)
improving the existing single hyper-heuristic project
scheduling research to construct a suitable solution
space for solving SRCPSP; and (3) bettering genetic
evolution of each subpopulation from a decision
ensemble with three different local searches in
corporation with discriminant mutation and discriminant
population renewal. In addition, a sequence voting
mechanism is designed to deal with collaborative
decision-making in the scheduling process for SRCPSP.
The benchmark PSPLIB is performed to verify the
advantage of the HH-EGP over heuristics,
meta-heuristics and the single hyper-heuristic
approaches",
- }
Genetic Programming entries for
HaoJie Chen
Guofu Ding
Sheng-feng Qin
Jian Zhang2
Citations