Advanced dwarf mongoose optimization for solving CEC 2011 and CEC 2017 benchmark problems

This paper proposes an improvement to the dwarf mongoose optimization (DMO) algorithm called the advanced dwarf mongoose optimization (ADMO) algorithm. The improvement goal is to solve the low convergence rate limitation of the DMO. This situation arises when the initial solutions are close to the o...

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Veröffentlicht in:	PloS one 2022-11, Vol.17 (11), p.e0275346-e0275346
Hauptverfasser:	Agushaka, Jeffrey O, Akinola, Olatunji, Ezugwu, Absalom E, Oyelade, Olaide N, Saha, Apu K
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Analysis Benchmarks Convergence Deep learning Evolutionary computation Exploitation Exploratory behavior Foraging behavior Health aspects Helogale parvula Hybrid composites Machine learning Neural networks Optimization Performance measurement Predation Reproductive behavior Social behavior Social behavior in animals Social networks Statistical analysis Traveling salesman problem
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