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Slime Mould Algorithm/Evidence
Method evidence record

Slime Mould Algorithm

The Slime Mould Algorithm (SMA) is a nature-inspired metaheuristic optimization technique introduced by Li et al. in 2020. It mimics the behavior of slime moulds, which spread and contract to find optimal food sources. SMA addresses complex optimization problems by simulating the adaptive foraging and spatial distribution patterns of these organisms.

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Slime Mould Algorithm
Taxonomic method record · ml-model / optimization
  • Li, S., Chen, H., Wang, M., Heidari, A. A., & Chakraborty, S. (2020). Slime mould algorithm: A new method for stochastic optimization. Future Generation Computer Systems, 111, 300-323. · DOI 10.1016/j.future.2020.03.055
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Related methods

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Taxonomic bucketAquila Optimizermachine-suggested · Relational suggestion, not evidence.Same method familyArithmetic Optimization Algorithmmachine-suggested · Relational suggestion, not evidence.Used in the same domainGenetic Algorithmmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketHarris Hawks Optimizationmachine-suggested · Relational suggestion, not evidence.Used in the same domainParticle Swarm Optimizationmachine-suggested · Relational suggestion, not evidence.

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Sources

1 recorded citation, copied from the method source record.

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