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Exposing the chimp optimization algorithm: A misleading metaheuristic technique with structural bias
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DOI：10.1016/j.asoc.2024.111574.png)
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摘要
En 中文
We conduct a comprehensive, component -based analysis of the highly cited chimp optimization algorithm (ChOA). Aside from disassembling ChOA into its constituent elements and establishing connections with analogous components in existing methodologies like particle swarm optimization, we scrutinize the application of metaphors that inspired ChOA. Our findings reveal that the idea introduced in ChOA has long been present in the metaheuristic literature, and the purported novelty in the algorithm primarily stems from the adoption of distinct terminologies based on new metaphors. Furthermore, experiments on the CEC2021 benchmark set and several standard benchmark functions involving their shifted versions reveal a structural bias in ChOA, which results in artificially high accuracy when fitting standard test functions but leads to weak performance when applied to shifted benchmarks. Finally, a critical mathematical analysis is provided to elucidate the fundamental reason behind the manifestation of this bias.
Keyword:
Metaheuristics
Component-based analysis
Design flaw
Structural bias
Shift invariance
期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
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