Proposal of Multimodal Program Optimization Benchmark and Its Application to Multimodal Genetic Programming
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- @InProceedings{Harada:2020:CEC,
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author = "Tomohiro Harada and Kei Murano and Ruck Thawonmas",
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title = "Proposal of Multimodal Program Optimization Benchmark
and Its Application to Multimodal Genetic Programming",
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booktitle = "2020 IEEE Congress on Evolutionary Computation, CEC
2020",
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year = "2020",
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editor = "Yaochu Jin",
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pages = "paper id24279",
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address = "internet",
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month = "19-24 " # jul,
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-7281-6929-3",
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DOI = "doi:10.1109/CEC48606.2020.9185705",
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abstract = "Multimodal program optimisations (MMPOs) have been
studied in recent years. MMPOs aims at obtaining
multiple optimal programs with different structures
simultaneously. This paper proposes novel MMPO
benchmark problems to evaluate the performance of the
multimodal program search algorithms. In particular, we
propose five MMPOs, which have different
characteristics, the similarity between optimal
programs, the complexity of optimal programs, and the
number of local optimal programs. We apply multimodal
genetic programming (MMGP) proposed in our previous
work to the proposed MMPOs to verify their difficulty
and effectiveness, and evaluate the performance of
MMGP. The experimental results reveal that the proposed
MMPOs are difficult and complex to obtain the global
and local optimal programs simultaneously as compared
to the conventional benchmark. In addition, the
experimental results clarify mechanisms to improve the
performance of MMGP.",
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notes = "https://wcci2020.org/
Tokyo Metropolitan University, Japan; Ritsumeikan
University, Japan.
Also known as \cite{9185705}",
- }
Genetic Programming entries for
Tomohiro Harada
Kei Murano
Ruck Thawonmas
Citations