Automated design of priority rules for resource-constrained project scheduling problem using surrogate-assisted genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{LUO:2023:swevo,
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author = "Jingyu Luo and Mario Vanhoucke and Jose Coelho",
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title = "Automated design of priority rules for
resource-constrained project scheduling problem using
surrogate-assisted genetic programming",
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journal = "Swarm and Evolutionary Computation",
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volume = "81",
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pages = "101339",
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year = "2023",
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ISSN = "2210-6502",
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DOI = "doi:10.1016/j.swevo.2023.101339",
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URL = "https://www.sciencedirect.com/science/article/pii/S2210650223001128",
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keywords = "genetic algorithms, genetic programming,
Resource-constrained project scheduling, Priority
rules, Surrogate models",
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abstract = "In the past few years, the genetic programming
approach (GP) has been successfully used by researchers
to design priority rules for the resource-constrained
project scheduling problem (RCPSP) thanks to its high
generalization ability and superior performance.
However, one of the main drawbacks of the GP is that
the fitness evaluation in the training process often
requires a very high computational effort. In order to
reduce the runtime of the training process, this
research proposed four different surrogate models for
the RCPSP. The experiment results have verified the
effectiveness and the performance of the proposed
surrogate models. It is shown that they achieve similar
performance as the original model with the same number
of evaluations and better performance with the same
runtime. We have also tested the performance of one of
our surrogate models with seven different population
sizes to show that the selected surrogate model
achieves similar performance for each population size
as the original model, even when the searching space is
sufficiently explored. Furthermore, we have
investigated the accuracy of our proposed surrogate
models and the size of the rules they designed. The
result reveals that all the proposed surrogate models
have high accuracy, and sometimes the rules found by
them have a smaller size compared with the original
model",
- }
Genetic Programming entries for
Jingyu Luo
Mario Vanhoucke
Jose Coelho
Citations