Ibraheem Abu Falahah1, Osama Al-Baik2, Saleh Alomari3, Gulnara Bektemyssova4, Saikat Gochhait5,6, Irina Leonova7, Om Parkash Malik8, Frank Werner9,*, Mohammad Dehghani10
CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3631-3678, 2024, DOI:10.32604/cmc.2024.053189
- 20 June 2024
Abstract This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization (FLO), which emulates the unique hunting behavior of frilled lizards in their natural habitat. FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards. The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases: (i) an exploration phase, which mimics the lizard’s sudden attack on its prey, and (ii) an exploitation phase, which simulates the lizard’s retreat to the treetops after feeding. To assess FLO’s efficacy in addressing optimization problems, its performance is rigorously tested on fifty-two… More >
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